Master's programme in Teacher Education (120 cp)

• Academic Work in Computer Science

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  • 19319701 Lecture
    Scientific Work/Research in Computer Science (Claudia Müller-Birn)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    Further information:

    https://www.mi.fu-berlin.de/w/SE/VorlesungWissenschaftlichesArbeiten2019

     

    Comments

    The lecture introduces students to scientific work. The essential forms of written and oral knowledge representation are described. It explains how to write computer science texts and how to read and examine them. Furthermore, students will be introduced to legal, ethical and philosophical problems of the sciences and in particular of computer science. Furthermore, problems of gender and diversity in computer science and in lectures will be presented and solution strategies will be discussed.

  • 19301710 Proseminar
    Undergraduate Seminar: Theoretical Computer Science (Katharina Klost)
    Schedule: Di 16:00-18:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    The proseminar delves more deeply into topics covered in the basic classes taught by the theory group. During the winter semester, we consider advanced topics from the theory of computability and of formal languates (in continuation of "Theory of Computation"); during the summer semester, we talk about algorithms (in continuation of "Algorithms, Data Structures, and Data Abstraction").

    Prerequisites

    two semesters of computer science, successful completion of "Theory of Computation"

    Suggested reading

    wird mit der Ankündigung bekannt gegeben

  • 19307117 Seminar / Undergraduate Course
    Seminar/Proseminar: Smart Homes and the World of IoT (Marius Max Wawerek)
    Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    This seminar focuses on various aspects of modern “Internet of Things” (IoT) systems. The main component will be applications and publications related to the area of the “Smart Home”. At the beginning of the seminar, suggested topics will be given, which will mainly deal with data analysis (both “normal” statistics and machine learning), security aspects and the usefulness of the Internet of Things or the “Smart Home”. You are also welcome to suggest your own topics, but they must be related to IoT systems. The topics should be worked on alone.

    About the procedure: This seminar takes place throughout the semester. There are few meetings, but these are mandatory. On the first date (14.04.2025) the list of topics will be handed out and discussed. In the next week (21.04.2025) there will be another opportunity to discuss topic suggestions. If you are interested in your own topic, please prepare a short (2-3 minutes) outline of your proposal. As in the third week (28.04.2025) the topics will be assigned.

    
    There will then be 3 presentation dates per person: the presentation of the literature research (19.05.2025), a short interim presentation (16.06.2025) and the final presentation on one of the dates in the period from 30.06.2025 - 14.07.2025. There will be no further meetings beyond this.

    This means that, depending on the number of participants, the following meetings are mandatory:

    • 14.04.2025
    • 21.04.2025
    • 19.05.2025
    • 16.06.2025
    • 30.06.2025
    • 07.07.2025
    • 14.07.2025

  • 19313310 Proseminar
    Undergraduate Seminar: Interactive Intelligent Systems - A Human-Centered Perspective (Malte Heiser)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Link to this course on the HCC website

     

    Comments

    In this Proseminar, we discuss research results from the field of Human Computer Interaction with a focus on computer science. In recent decades, this area has changed extensively, mainly through technological innovations. We primarily consider these changed interactions between one or more people and one or more computers.

    This time we will focus specifically on interactions with large language models (LLMs). We will explore new ways that these tools allow us to interact with technology. We will also consider the implications of generative AI for users and society at large.

    In this course, we will cover a selection of important paper on pioneering work in HCI. Each semester, the focus of the more recent work might change. Each week, one student will present one important approach, and we will discuss it in class. Within presentations students have to introduce the assigned readings, will discuss them in context and will derive new, possible topics. Articles are chosen because they describe either a specific sub-­-area, represent the first article in a specific area, or introduce different approaches in the area.

    Suggested reading

    Wird bei der Vorbesprechung im April bekanntgegeben.

  • 19331617 Seminar / Undergraduate Course
    Seminar/Proseminar: Information-theoretical principles of ML (Gerhard Wunder)
    Schedule: Fr 14:00-16:00 (Class starts on: 2025-04-25)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    Recently, artificial intelligence and machine learning (AI/ML) has emerged as a valuable tool in the field of communication and signal processing. It is therefore natural to extend the investigations to the field of physical layer security and privacy. This field is still in its infancy with some very preliminary results on wiretap channel code design, feature extraction of wireless channels and a growing part of contributions to privacy-preserving, distributed AI/ML. This seminar will teach the latest advances and synergies between the broad fields of AI/ML and secure communications.

    Keywords: ML overview, basic tools, universal approximation, deep learning, stochastic gradient, acceleration strategies, deep convolutional networks, feature extraction, classification, mutual information neural network estimation, structured sparsity in convolutional neural networks, matrix decompositions

     

  • 19334617 Seminar / Undergraduate Course
    Seminar/Proseminar: How to Startup (Tim Landgraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    This seminar explores the multifaceted world of startups, providing students with a comprehensive understanding of what it takes to succeed in a dynamic and competitive environment. Topics covered include team composition, market analysis, investment logic, emerging trends (such as AI), and common pitfalls faced by startups.
    Unlike traditional seminars, this course emphasizes practical engagement. Students will work on preparing concise "Impulsvorträge" (short, 15-minute talks) on specific startup-related topics. These presentations will draw from a variety of sources, including:
    
    * Web Research: Gathering insights from industry reports, blogs, and articles.
    * Interviews: Engaging with actual startups to gain firsthand knowledge and perspectives.
    * Trend Analysis: Examining current innovations and disruptions in the startup ecosystem.

    
    Each talk will serve as the starting point for an interactive discussion, stimulating deeper understanding and diverse viewpoints among participants.
    This seminar is ideal for students who are curious about entrepreneurship and eager to explore how startups operate, grow, and navigate challenges in today's fast-paced world.

     

  • 19336717 Seminar / Undergraduate Course
    Active learning, uncertainty and XAI with applications in biomedicine (Katharina Baum)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    In this advanced seminar, we will discuss a variety of methods for machine learning. The focus will be on approaches to active learning, uncertainty estimation and its utilization, as well as methods for explaining models. The application and development of these methods for biomedical research questions will be explored using current research papers.

    Examples of approaches covered include:

    • selective sampling
    • SHAP values
    • Gaussian ensemble models
    • Bayesian neural networks

    The seminar will primarily be conducted in English, but of course, you are welcome to ask questions in German.

• Operating and Communication Systems

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  • 19300701 Lecture
    Operating and Communication Systems (Larissa Groth)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    The module operating and communication systems closes the gap between the hardware of a computer and the applications.

    We will cover the following topics::

    • I/O systems
    • DMA/PIO
    • Interrupt handling
    • Buffers
    • Processes/threads
    • Virtual memory
    • UNIX and Windows
    • Shells
    • Utilities
    • Peripherals and networking
    • Networks
    • Media
    • Media access
    • Protocols
    • Reference models
    • TCP/IP
    • The Internet

    Suggested reading

    • Andrew S. Tanenbaum: Computerarchitektur, 5.Auflage, Pearson Studium, 2006
    • English: Andrew S. Tanenbaum (with contributions from James R. Goodman):
    • Structured Computer Organization, 4th Ed., Prentice Hall International, 2005.

  • 19300704 PC-based Seminar
    Practice seminar for Operating and Communication Systems (Larissa Groth)
    Schedule: Mo 10:00-12:00, Mo 14:00-16:00, Di 10:00-12:00, Di 12:00-14:00, Mi 08:00-10:00, Mi 12:00-14:00, Mi 14:00-16:00, Do 10:00-12:00, Do 12:00-14:00, Do 16:00-18:00, Fr 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/K38 Rechnerpoolraum (Takustr. 9)
    

    Comments

    Begleitveranstaltung zur Vorlesung 19300701

• Software Project: Applied Computer Science A

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  • 19308412 Project Seminar
    Software Project: Data Management (Agnès Voisard)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-05)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students in the Master's or Bachelor's programme

     

    Prerequisites

    Good programming skills, introduction to database systems.

    Comments

    Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Corporate Semantic Web

    Further information can be found on the course website

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

    Suggested reading

    Corporate Semantic Web

  • 19323612 Project Seminar
    The AMOS Project (Lutz Prechelt)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Educational objectives and competencies

    • Students learn about software products and software development in an industry context
    • Students learn about agile methods, in particular Scrum and Extreme Programming
    • Students learn about open source software development and its underlying principles
    • Students gain practical hands-on experience with a Scrum process and XP technical practices

    Target group

    Students of computer science (and related fields). If you want to play the software developer role, you should have had practical programming experience. This is not a course to learn programming.

    Language

    English (lectures in English, team meeting German or English by choice of student team)

    Grading

    • Software developer
      • 10% of grade: 5 class quizzes, each consisting of 5 questions at 2 points each
      • 90% of grade: Weekly project work

    Other

    • SWS: 4 SWS (2 SWS lecture, 2 SWS team meeting)
    • Semester: Every semester
    • Modality: Online, across multiple universities
    • Tags: Scrum

     

    Comments

    This course teaches agile methods (Scrum and XP) and open source tools using a single semester-long project. It takes place online and across multiple universities. Topics covered are:

    • Agile methods and related software development processes
    • Scrum roles, process practices, including product and engineering management
    • Technical practices like refactoring, continuous integration, and test-driven development
    • Principles and best practices of open source software development

    The project is a software development project in which each student team works with an industry partner who provides the idea for the project. This is a practical hands-on experience.

    Students play the role of a software developer. In this role, students estimate the effort for requirements and implement them. Students must have prior software development experience.

    Students will be organized into teams of 7-9 people, combining one Scrum master with two product owners with six software developers.

    An industry partner will provide requirements to be worked out in detail by the product owners and to be realized by the software developers. The available projects will be presented in the run-up to the course.

    Class consists of a 90 min. lecture followed by a 90 min. team meeting. Rooms and times for team meetings are assigned at the beginning of the semester. You must be able to regularly participate in the team meetings. If you can't, do not sign up for this course.

    Attention: this course is organized externally and additional sign-up steps are required. Sign-up and further course information are available through a Google spreadsheet at https://amos.uni1.de – please declare your interest by filling out the course interest declaration survey as soon as it opens.

    Suggested reading

    http://goo.gl/5Wqnr7

  • 19329912 Project Seminar
    Software Project: Secure Identity (Volker Roth)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Comments

    Die Aufgabe wird die Entwicklung einer Software sein. Es wird um sichere Softwareentwicklung gehen. Die Aufgabe wird in Gruppenarbeit gelöst.

  • 19334212 Project Seminar
    Softwareproject: Machine Learning and Explainability for Improved (Cancer) Treatment (Pauline Hiort)
    Schedule: Di 15:00-17:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-26)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    In the software project, we will implement, train, and evaluate various machine learning (ML) methods. The focus of the project is on neural networks (NN) and their explainability. We will compare the methods with different baseline models, such as regression models. The various ML methods will be applied to a specific dataset, e.g., for predicting drug combinations for cancer treatment, and evaluated accordingly. The dataset will be prepared by us and analyzed using the implemented methods. Additionally, we will focus on explainability to ensure that the predictions of the ML models are understandable and interpretable. For this purpose, we will integrate appropriate explainability techniques to better understand and visualize the decision-making processes of the models.

    The programming language is Python, and we plan to use modern Python modules for ML like scikit-learn, and PyTorch. Good Python skills are required. The goal is to create a Python package that provides reusable code for preprocessing, training ML models, and evaluating results with documentation (e.g., using Sphinx) for the specific use case. The software project takes place throughout the semester and can also be conducted in English.

  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Software Project: Applied Computer Science B

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  • 19308412 Project Seminar
    Software Project: Data Management (Agnès Voisard)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-05)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students in the Master's or Bachelor's programme

     

    Prerequisites

    Good programming skills, introduction to database systems.

    Comments

    Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Corporate Semantic Web

    Further information can be found on the course website

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

    Suggested reading

    Corporate Semantic Web

  • 19323612 Project Seminar
    The AMOS Project (Lutz Prechelt)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Educational objectives and competencies

    • Students learn about software products and software development in an industry context
    • Students learn about agile methods, in particular Scrum and Extreme Programming
    • Students learn about open source software development and its underlying principles
    • Students gain practical hands-on experience with a Scrum process and XP technical practices

    Target group

    Students of computer science (and related fields). If you want to play the software developer role, you should have had practical programming experience. This is not a course to learn programming.

    Language

    English (lectures in English, team meeting German or English by choice of student team)

    Grading

    • Software developer
      • 10% of grade: 5 class quizzes, each consisting of 5 questions at 2 points each
      • 90% of grade: Weekly project work

    Other

    • SWS: 4 SWS (2 SWS lecture, 2 SWS team meeting)
    • Semester: Every semester
    • Modality: Online, across multiple universities
    • Tags: Scrum

     

    Comments

    This course teaches agile methods (Scrum and XP) and open source tools using a single semester-long project. It takes place online and across multiple universities. Topics covered are:

    • Agile methods and related software development processes
    • Scrum roles, process practices, including product and engineering management
    • Technical practices like refactoring, continuous integration, and test-driven development
    • Principles and best practices of open source software development

    The project is a software development project in which each student team works with an industry partner who provides the idea for the project. This is a practical hands-on experience.

    Students play the role of a software developer. In this role, students estimate the effort for requirements and implement them. Students must have prior software development experience.

    Students will be organized into teams of 7-9 people, combining one Scrum master with two product owners with six software developers.

    An industry partner will provide requirements to be worked out in detail by the product owners and to be realized by the software developers. The available projects will be presented in the run-up to the course.

    Class consists of a 90 min. lecture followed by a 90 min. team meeting. Rooms and times for team meetings are assigned at the beginning of the semester. You must be able to regularly participate in the team meetings. If you can't, do not sign up for this course.

    Attention: this course is organized externally and additional sign-up steps are required. Sign-up and further course information are available through a Google spreadsheet at https://amos.uni1.de – please declare your interest by filling out the course interest declaration survey as soon as it opens.

    Suggested reading

    http://goo.gl/5Wqnr7

  • 19329912 Project Seminar
    Software Project: Secure Identity (Volker Roth)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Comments

    Die Aufgabe wird die Entwicklung einer Software sein. Es wird um sichere Softwareentwicklung gehen. Die Aufgabe wird in Gruppenarbeit gelöst.

  • 19334212 Project Seminar
    Softwareproject: Machine Learning and Explainability for Improved (Cancer) Treatment (Pauline Hiort)
    Schedule: Di 15:00-17:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-26)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    In the software project, we will implement, train, and evaluate various machine learning (ML) methods. The focus of the project is on neural networks (NN) and their explainability. We will compare the methods with different baseline models, such as regression models. The various ML methods will be applied to a specific dataset, e.g., for predicting drug combinations for cancer treatment, and evaluated accordingly. The dataset will be prepared by us and analyzed using the implemented methods. Additionally, we will focus on explainability to ensure that the predictions of the ML models are understandable and interpretable. For this purpose, we will integrate appropriate explainability techniques to better understand and visualize the decision-making processes of the models.

    The programming language is Python, and we plan to use modern Python modules for ML like scikit-learn, and PyTorch. Good Python skills are required. The goal is to create a Python package that provides reusable code for preprocessing, training ML models, and evaluating results with documentation (e.g., using Sphinx) for the specific use case. The software project takes place throughout the semester and can also be conducted in English.

  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Academic Work in Applied Computer Science A

  0089cA1.25
  • 19303811 Seminar
    Project Seminar: Data Management (Muhammed-Ugur Karagülle)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-04-17)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirement

    ALP I-III, Foundations of Datenbase Systems, good programming knowledge.

    Comments

    Content

    A project seminar serves as preparation of a thesis (bachelor or master) in the AGDB. The focus of this project seminar lies on the analysis and visualization of medical data. Additionally, we will realize a small software project.

    Suggested reading

    Wird bekannt gegeben.

  • 19305811 Seminar
    Seminar: Contributions to Software Engineering (Lutz Prechelt)
    Schedule: Do 16:00-18:00 (Class starts on: 2025-04-17)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students of Computer Science (also Minor).

    In case you are interested, please contact an adecuate group member with a topic suggestion or request.

    As this lecture is offered continuously, attendance may also start any time during the semester.

    Requirements

    Any computer science student having attended the lecture Software Engineering (Softwaretechnik).

    It may become necessary to deal with materials from the lecture Empirical Evaluation in Informatics (Empirische Bewertung in der Informatik).

    Homepage

    http://www.inf.fu-berlin.de/w/SE/SeminarBeitraegeZumSE

    Comments

    Content

    This is a reseach seminar: normally the presentations are supposed to advance current research projects. Thus, there are, generally speaking, three possible types of topics:

    • published or current research projects from one of the areas in which our software engineering group works
    • especially good specific research projects (or other knowledge) from other areas of software engineering or adjacent areas of computer science
    • basis topics from important areas of software engineering or adjacent disciplines such as psychology, sociology, pedagogics, economics as well as their methods.

    There is no exact restriction of topics though; almost anything is possible.

    Suggested reading

    Je nach Wahl des Vortragsthemas

  • 19307117 Seminar / Undergraduate Course
    Seminar/Proseminar: Smart Homes and the World of IoT (Marius Max Wawerek)
    Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    This seminar focuses on various aspects of modern “Internet of Things” (IoT) systems. The main component will be applications and publications related to the area of the “Smart Home”. At the beginning of the seminar, suggested topics will be given, which will mainly deal with data analysis (both “normal” statistics and machine learning), security aspects and the usefulness of the Internet of Things or the “Smart Home”. You are also welcome to suggest your own topics, but they must be related to IoT systems. The topics should be worked on alone.

    About the procedure: This seminar takes place throughout the semester. There are few meetings, but these are mandatory. On the first date (14.04.2025) the list of topics will be handed out and discussed. In the next week (21.04.2025) there will be another opportunity to discuss topic suggestions. If you are interested in your own topic, please prepare a short (2-3 minutes) outline of your proposal. As in the third week (28.04.2025) the topics will be assigned.

    
    There will then be 3 presentation dates per person: the presentation of the literature research (19.05.2025), a short interim presentation (16.06.2025) and the final presentation on one of the dates in the period from 30.06.2025 - 14.07.2025. There will be no further meetings beyond this.

    This means that, depending on the number of participants, the following meetings are mandatory:

    • 14.04.2025
    • 21.04.2025
    • 19.05.2025
    • 16.06.2025
    • 30.06.2025
    • 07.07.2025
    • 14.07.2025

  • 19328217 Seminar / Undergraduate Course
    Seminar/Proseminar: New Trends in Information Systems (Agnès Voisard)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A3/SR 119 (Arnimallee 3-5)
    

    Comments

    This seminar aims at studying recent trends in data management. Among others, we will look at two emerging topics, namely Location-Based Services (LBS) and Event-Based Services (EBS).

    Event-based Systems (EBS) are part of many current applications such as business activity monitoring, stock tickers, facility management, data streaming, or security. In the past years, the topic has gained increasing attention from both the industrial and the academic community. Current research concentrates of diverse aspects that range from event capture (incoming data) to response triggering. This seminar aims at studying some of the current trends in Event-based Systems with a strong focus on models and design. Location-based services are now often part of every day's life through applications such as navigation assistants in the public or private transportation domain. The underlying technology deals with many different aspects, such as location detection, information retrieval, or privacy. More recently, aspects such as user context and preferences were considered in order to send users more personalized information.

    A solid background in databases is required, typically a database course at a bachelor level.

    Suggested reading

    Wird bekannt gegeben.

  • 19333311 Seminar
    Seminar: Continual Learning (Manuel Heurich)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    

    Comments

    This seminar focuses on recent advances in ‘Continual Learning’, an increasingly important field within machine learning. Continual Learning tackles the problem of drifting data in input space and changes between input and target distribution. Static models drop significantly in performance when data distributions are subject to change over time. We will cover recent approaches that tackle this problem from different angles. This seminar explores the training of adaptive models that can perform strongly in highly volatile domains.

  • 19334617 Seminar / Undergraduate Course
    Seminar/Proseminar: How to Startup (Tim Landgraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    This seminar explores the multifaceted world of startups, providing students with a comprehensive understanding of what it takes to succeed in a dynamic and competitive environment. Topics covered include team composition, market analysis, investment logic, emerging trends (such as AI), and common pitfalls faced by startups.
    Unlike traditional seminars, this course emphasizes practical engagement. Students will work on preparing concise "Impulsvorträge" (short, 15-minute talks) on specific startup-related topics. These presentations will draw from a variety of sources, including:
    
    * Web Research: Gathering insights from industry reports, blogs, and articles.
    * Interviews: Engaging with actual startups to gain firsthand knowledge and perspectives.
    * Trend Analysis: Examining current innovations and disruptions in the startup ecosystem.

    
    Each talk will serve as the starting point for an interactive discussion, stimulating deeper understanding and diverse viewpoints among participants.
    This seminar is ideal for students who are curious about entrepreneurship and eager to explore how startups operate, grow, and navigate challenges in today's fast-paced world.

     

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

  • 19336717 Seminar / Undergraduate Course
    Active learning, uncertainty and XAI with applications in biomedicine (Katharina Baum)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    In this advanced seminar, we will discuss a variety of methods for machine learning. The focus will be on approaches to active learning, uncertainty estimation and its utilization, as well as methods for explaining models. The application and development of these methods for biomedical research questions will be explored using current research papers.

    Examples of approaches covered include:

    • selective sampling
    • SHAP values
    • Gaussian ensemble models
    • Bayesian neural networks

    The seminar will primarily be conducted in English, but of course, you are welcome to ask questions in German.

• Academic Work in Applied Computer Science B

  0089cA1.26
  • 19303811 Seminar
    Project Seminar: Data Management (Muhammed-Ugur Karagülle)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-04-17)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Requirement

    ALP I-III, Foundations of Datenbase Systems, good programming knowledge.

    Comments

    Content

    A project seminar serves as preparation of a thesis (bachelor or master) in the AGDB. The focus of this project seminar lies on the analysis and visualization of medical data. Additionally, we will realize a small software project.

    Suggested reading

    Wird bekannt gegeben.

  • 19305811 Seminar
    Seminar: Contributions to Software Engineering (Lutz Prechelt)
    Schedule: Do 16:00-18:00 (Class starts on: 2025-04-17)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students of Computer Science (also Minor).

    In case you are interested, please contact an adecuate group member with a topic suggestion or request.

    As this lecture is offered continuously, attendance may also start any time during the semester.

    Requirements

    Any computer science student having attended the lecture Software Engineering (Softwaretechnik).

    It may become necessary to deal with materials from the lecture Empirical Evaluation in Informatics (Empirische Bewertung in der Informatik).

    Homepage

    http://www.inf.fu-berlin.de/w/SE/SeminarBeitraegeZumSE

    Comments

    Content

    This is a reseach seminar: normally the presentations are supposed to advance current research projects. Thus, there are, generally speaking, three possible types of topics:

    • published or current research projects from one of the areas in which our software engineering group works
    • especially good specific research projects (or other knowledge) from other areas of software engineering or adjacent areas of computer science
    • basis topics from important areas of software engineering or adjacent disciplines such as psychology, sociology, pedagogics, economics as well as their methods.

    There is no exact restriction of topics though; almost anything is possible.

    Suggested reading

    Je nach Wahl des Vortragsthemas

  • 19307117 Seminar / Undergraduate Course
    Seminar/Proseminar: Smart Homes and the World of IoT (Marius Max Wawerek)
    Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    This seminar focuses on various aspects of modern “Internet of Things” (IoT) systems. The main component will be applications and publications related to the area of the “Smart Home”. At the beginning of the seminar, suggested topics will be given, which will mainly deal with data analysis (both “normal” statistics and machine learning), security aspects and the usefulness of the Internet of Things or the “Smart Home”. You are also welcome to suggest your own topics, but they must be related to IoT systems. The topics should be worked on alone.

    About the procedure: This seminar takes place throughout the semester. There are few meetings, but these are mandatory. On the first date (14.04.2025) the list of topics will be handed out and discussed. In the next week (21.04.2025) there will be another opportunity to discuss topic suggestions. If you are interested in your own topic, please prepare a short (2-3 minutes) outline of your proposal. As in the third week (28.04.2025) the topics will be assigned.

    
    There will then be 3 presentation dates per person: the presentation of the literature research (19.05.2025), a short interim presentation (16.06.2025) and the final presentation on one of the dates in the period from 30.06.2025 - 14.07.2025. There will be no further meetings beyond this.

    This means that, depending on the number of participants, the following meetings are mandatory:

    • 14.04.2025
    • 21.04.2025
    • 19.05.2025
    • 16.06.2025
    • 30.06.2025
    • 07.07.2025
    • 14.07.2025

  • 19328217 Seminar / Undergraduate Course
    Seminar/Proseminar: New Trends in Information Systems (Agnès Voisard)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A3/SR 119 (Arnimallee 3-5)
    

    Comments

    This seminar aims at studying recent trends in data management. Among others, we will look at two emerging topics, namely Location-Based Services (LBS) and Event-Based Services (EBS).

    Event-based Systems (EBS) are part of many current applications such as business activity monitoring, stock tickers, facility management, data streaming, or security. In the past years, the topic has gained increasing attention from both the industrial and the academic community. Current research concentrates of diverse aspects that range from event capture (incoming data) to response triggering. This seminar aims at studying some of the current trends in Event-based Systems with a strong focus on models and design. Location-based services are now often part of every day's life through applications such as navigation assistants in the public or private transportation domain. The underlying technology deals with many different aspects, such as location detection, information retrieval, or privacy. More recently, aspects such as user context and preferences were considered in order to send users more personalized information.

    A solid background in databases is required, typically a database course at a bachelor level.

    Suggested reading

    Wird bekannt gegeben.

  • 19333311 Seminar
    Seminar: Continual Learning (Manuel Heurich)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    

    Comments

    This seminar focuses on recent advances in ‘Continual Learning’, an increasingly important field within machine learning. Continual Learning tackles the problem of drifting data in input space and changes between input and target distribution. Static models drop significantly in performance when data distributions are subject to change over time. We will cover recent approaches that tackle this problem from different angles. This seminar explores the training of adaptive models that can perform strongly in highly volatile domains.

  • 19334617 Seminar / Undergraduate Course
    Seminar/Proseminar: How to Startup (Tim Landgraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

    Comments

    This seminar explores the multifaceted world of startups, providing students with a comprehensive understanding of what it takes to succeed in a dynamic and competitive environment. Topics covered include team composition, market analysis, investment logic, emerging trends (such as AI), and common pitfalls faced by startups.
    Unlike traditional seminars, this course emphasizes practical engagement. Students will work on preparing concise "Impulsvorträge" (short, 15-minute talks) on specific startup-related topics. These presentations will draw from a variety of sources, including:
    
    * Web Research: Gathering insights from industry reports, blogs, and articles.
    * Interviews: Engaging with actual startups to gain firsthand knowledge and perspectives.
    * Trend Analysis: Examining current innovations and disruptions in the startup ecosystem.

    
    Each talk will serve as the starting point for an interactive discussion, stimulating deeper understanding and diverse viewpoints among participants.
    This seminar is ideal for students who are curious about entrepreneurship and eager to explore how startups operate, grow, and navigate challenges in today's fast-paced world.

     

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

  • 19336717 Seminar / Undergraduate Course
    Active learning, uncertainty and XAI with applications in biomedicine (Katharina Baum)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: T9/051 Seminarraum (Takustr. 9)
    

    Comments

    In this advanced seminar, we will discuss a variety of methods for machine learning. The focus will be on approaches to active learning, uncertainty estimation and its utilization, as well as methods for explaining models. The application and development of these methods for biomedical research questions will be explored using current research papers.

    Examples of approaches covered include:

    • selective sampling
    • SHAP values
    • Gaussian ensemble models
    • Bayesian neural networks

    The seminar will primarily be conducted in English, but of course, you are welcome to ask questions in German.

  • 19337517 Seminar / Undergraduate Course
    Seminar/Proseminar: Time Series Learning (Manuel Heurich)
    Schedule: Mo 10:00-12:00 (Class starts on: 2025-04-14)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    

    Comments

    This seminar focuses on Machine Learning approaches that specialize in sequential data. Most real-world data is acquired over time. Moreover, most of the available data is not image data. We will discuss works before the Transformer era (e.g., RNNs, LSTMs) and highlight their strengths and weaknesses outside the Computer Vision domain. More recently, transformer-based approaches have outperformed earlier methods. We selectively pick works that highlight their strength in knowledge discovery on sequential data. With the strong trend towards powerful multi-modal models, the seminar aims to introduce state-of-the-art methods to produce robust embeddings based on Time Series data.

• Current research topics in Applied Computer Science

  0089cA1.27
  • 19302801 Lecture
    Applied Biometrics (Andreas Wolf)
    Schedule: Mo 08:00-10:00 (Class starts on: 2025-04-14)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Die Lehrveranstaltung soll am Freitag den 12. April beginnen.

    Das Vorlesungsskript liegt unter

    https://drive.google.com/drive/folders/0B7NhYbv9QewkRkk2WVRuM2Rqd00?usp=sharing

    Webex Link zu der Veranstaltung:

    Meeting-Link: https://fu-berlin.webex.com/fu-berlin/j.php?MTID=m2cc50d96918fcaeb09f3c36a264f4f29

    Meeting-ID: 121 079 7504

    Meeting-Password: mCwDw274PS8

    Comments

    The lecture held by Dr. Andreas Wolf (from the Bundesdruckerei) He will give a broad overview of biometric processes and applications. He will also address the current issues with ePassports and new electronic identity cards.

    The course aims to include:

    • General structure of biometric systems
    • Features of biometric modalities
    • IT security and risk assessment
    • Errors in biometric processes
    • Fingerprinting
    • Facial and iris recognition
    • Speaker recognition and other modalities
    • Standards
    • ePassport

    Next to the theoretical foundations of biometric modalities, the students are to develop the ability to assess the applicability of biometrics in various scenarios.

  • 19325301 Lecture
    Cluster Computing (Barry Linnert)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    • Computer Science Master students

    Requirements

    • Experience with computers and software as well as programing skills.

    Language

    • The course language is German (or English if requested).
    • The exam will be formulated in German, but answers may be given in English, too.

    Credits & Exams

    The criteria for gaining credits are

    • active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
    • passing of the exam

    Website

    https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

     

    Comments

    Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented.

    Suggested reading

    • Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
    • Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
    • Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
    • Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
    • Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

  • 19327401 Lecture
    Image- and video coding (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    This course introduces the most important concepts and algorithms that are used in modern image and video coding approaches. We will particularly focus on techniques that are found in current international video coding standards.

    In a short first part, we introduce the so-called raw data formats, which are used as input and output formats of image and video codecs. This part covers the following topics:

    • Colour spaces and their relation to human visual perception
    • Transfer functions (gamma encoding)
    • Why do we use the YCbCr format?

    The second part of the course deals with still image coding and includes the following topics:

    • The start: How does JPEG work?
    • Why do we use the Discrete Cosine Transform?
    • Efficient coding of transform coefficients
    • Prediction of image blocks
    • Adaptive block partitioning
    • How do we take decisions in an encoder?
    • Optimized quantization

    In the third part, we discuss approaches that make video coding much more efficient than coding all pictures using still image coding techniques:

    • Motion-compensated prediction
    • Coding of motion vectors
    • Algorithms for motion estimation
    • Sub-sample accurate motion vectors and interpolation filters
    • Usage of multiple reference pictures
    • What are B pictures and why do we use them?
    • Deblocking and deringing filters
    • Efficient temporal coding structures

    In the exercises, we will implement our own image codec (in a gradual manner). We may extend it to a simple video codec.

     

    Suggested reading

    • Bull, D. R., “Communicating Pictures: A Course in Image and Video Coding,” Elsevier, 2014.
    • Ohm, J.-R., “Multimedia Signal Coding and Transmission,” Springer, 2015.
    • Wien, M., “High Efficiency Video Coding — Coding Tools and Specifications,” Springer 2014.
    • Sze, V., Budagavi, M., and Sullivan, G. J. (eds.), “High Efficiency Video Coding (HEVC): Algorithm and Architectures,” Springer, 2014.
    • Wiegand, T. and Schwarz, H., "Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 4, no. 1–2, 2011.
    • Schwarz, H. and Wiegand, T., “Video Coding: Part II of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 10, no. 1–3, 2016.

  • 19331101 Lecture
    Human Centered Data Science (Claudia Müller-Birn)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    [link HCC-Webseite aktuelles Semester]

    Comments

    In recent years, data science has developed rapidly, primarily due to the progress in machine learning. This development has opened up new opportunities in a variety of social, scientific, and technological areas. From the experience of recent years, however, it is becoming increasingly clear that the concentration on purely statistical and numerical aspects in data science fails to capture social nuances or take ethical criteria into account. The research area Human-Centered Data Science closes this gap at the intersection of Human-Computer Interaction (HCI), Computer-Supported Cooperative Work (CSCW), Human Computation, and the statistical and numerical techniques of Data Science.

    Human-Centered Data Science (HCDS) focuses on fundamental principles of data science and its human implications, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness, and accountability; data provenance, curation, preservation, and reproducibility; user experience design and research for big data; human computation; effective oral, written, and visual scientific communication; and societal impacts of data science.

    At the end of this course, students will understand the main concepts, theories, practices, and different perspectives on which data can be collected and manipulated. Furthermore, students will be able to realize the impact of current technological developments may have on society.

    This course curriculum was initially developed by Jonathan T. Morgan, Cecilia Aragon, Os Keyes, and Brock Craft. We have adapted the curriculum for the European context and our specific understanding of the field.

    Suggested reading

    Aragon, C. M., Hutto, C., Echenique, A., Fiore-Gartland, B., Huang, Y., Kim, J., et al. (2016). Developing a Research Agenda for Human-Centered Data Science. (pp. 529–535). Presented at the CSCW Companion, New York, New York, USA: ACM Press. http://doi.org/10.1145/2818052.2855518

    Baumer, E. P. (2017). Toward human-centered algorithm design:. Big Data & Society, 4(2), 205395171771885. http://doi.org/10.1177/2053951717718854

    Kogan, M., Halfaker, A., Guha, S., Aragon, C., Muller, M., & Geiger, S. (2020, January). Mapping Out Human-Centered Data Science: Methods, Approaches, and Best Practices. In Companion of the 2020 ACM International Conference on Supporting Group Work (pp. 151-156).

  • 19333101 Lecture
    Cybersecurity and AI II: Explainability (Gerhard Wunder)
    Schedule: Mo 12:00-14:00, Di 10:00-12:00, Fr 12:00-14:00 (Class starts on: 2025-04-15)
    Location: 1.3.21 Seminarraum T1 (Arnimallee 14)
    
  • 19333701 Lecture
    Ethics and Epistemology of AI (Christoph Benzmüller)
    Schedule: -
    Location: keine Angabe
    

    Comments

    The course Ethics and Epistemology of AI will be offered again in summer 2025 in cooperation with the TU Berlin (Prof. Sabine Ammon) and U Bamberg. It will bring together an interdisciplinary mix of students from different institutions, including BUA Berlin and Erasmus students.

    Innovative. Experimental. Interdisciplinary.

    More Information: https://www.tu.berlin/en/philtech/study-and-teaching/courses/ethics-and-epistemology-of-ai

    Information for interested students:

    • The course primarily targets masters students with interest in assessing critical aspects of latest artificial intelligence technology and to explore possible solutions and improvements; the course is also part of the Berlin Ethics certificate.
    • Online on-boarding meetings are offered on April 16 (14:15) and April 23 (14:15). The link will be communicated.
    • The course starts immediately after easter with a small pre-exercise to be conducted by each participant individually.
    • Very important is that students then meet for one week in person in Berlin from 28. April to 2. Mai. Participation in this intensive (but also great fun) daily event at TU Berlin is crucial, since it is here where the interdisciplinary and interinstitutional working teams are formed and where the working topics are defined in interaction with the supervisors.
    • After the intensive meeting in Berlin the teams work independently  via the internet; the group typically meets online with their supervisors each Wednesday (early afternoon).
    • Group project presentations are scheduled for June 11; after this date the groups then work on their joint final report.
    • This course is challenging but also fun, and you can expect to build an international network of other students who are interested in assessing critical aspects of AI.

    Contact for administrational questions at TU Berlin: Leon Dirmeier (dirmeier@campus.tu-berlin.de)

  • 19302802 Practice seminar
    Practice seminar for Applied Biometrics (Andreas Wolf)
    Schedule: Mo 10:00-12:00 (Class starts on: 2025-04-14)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    
  • 19325302 Practice seminar
    Practice seminar for Cluster Computing (Barry Linnert)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: T9/K44 Rechnerpoolraum (Takustr. 9)
    
  • 19327402 Practice seminar
    Practice seminar for image- und video coding (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19331102 Practice seminar
    Practice Session on Human Centered Data Science (Claudia Müller-Birn)
    Schedule: Di 16:00-18:00 (Class starts on: 2025-04-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19333102 Practice seminar
    Practice seminar for Cybersecurity and AI II (Gerhard Wunder)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-28)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    
  • 19333702 Practice seminar
    Ethics and Epistemology of AI (Christoph Benzmüller)
    Schedule: -
    Location: keine Angabe
    

• Special Aspects of Applied Computer Science

  0089cA1.28
  • 19302801 Lecture
    Applied Biometrics (Andreas Wolf)
    Schedule: Mo 08:00-10:00 (Class starts on: 2025-04-14)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Die Lehrveranstaltung soll am Freitag den 12. April beginnen.

    Das Vorlesungsskript liegt unter

    https://drive.google.com/drive/folders/0B7NhYbv9QewkRkk2WVRuM2Rqd00?usp=sharing

    Webex Link zu der Veranstaltung:

    Meeting-Link: https://fu-berlin.webex.com/fu-berlin/j.php?MTID=m2cc50d96918fcaeb09f3c36a264f4f29

    Meeting-ID: 121 079 7504

    Meeting-Password: mCwDw274PS8

    Comments

    The lecture held by Dr. Andreas Wolf (from the Bundesdruckerei) He will give a broad overview of biometric processes and applications. He will also address the current issues with ePassports and new electronic identity cards.

    The course aims to include:

    • General structure of biometric systems
    • Features of biometric modalities
    • IT security and risk assessment
    • Errors in biometric processes
    • Fingerprinting
    • Facial and iris recognition
    • Speaker recognition and other modalities
    • Standards
    • ePassport

    Next to the theoretical foundations of biometric modalities, the students are to develop the ability to assess the applicability of biometrics in various scenarios.

  • 19325301 Lecture
    Cluster Computing (Barry Linnert)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    • Computer Science Master students

    Requirements

    • Experience with computers and software as well as programing skills.

    Language

    • The course language is German (or English if requested).
    • The exam will be formulated in German, but answers may be given in English, too.

    Credits & Exams

    The criteria for gaining credits are

    • active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
    • passing of the exam

    Website

    https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

     

    Comments

    Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented.

    Suggested reading

    • Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
    • Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
    • Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
    • Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
    • Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

  • 19327401 Lecture
    Image- and video coding (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    This course introduces the most important concepts and algorithms that are used in modern image and video coding approaches. We will particularly focus on techniques that are found in current international video coding standards.

    In a short first part, we introduce the so-called raw data formats, which are used as input and output formats of image and video codecs. This part covers the following topics:

    • Colour spaces and their relation to human visual perception
    • Transfer functions (gamma encoding)
    • Why do we use the YCbCr format?

    The second part of the course deals with still image coding and includes the following topics:

    • The start: How does JPEG work?
    • Why do we use the Discrete Cosine Transform?
    • Efficient coding of transform coefficients
    • Prediction of image blocks
    • Adaptive block partitioning
    • How do we take decisions in an encoder?
    • Optimized quantization

    In the third part, we discuss approaches that make video coding much more efficient than coding all pictures using still image coding techniques:

    • Motion-compensated prediction
    • Coding of motion vectors
    • Algorithms for motion estimation
    • Sub-sample accurate motion vectors and interpolation filters
    • Usage of multiple reference pictures
    • What are B pictures and why do we use them?
    • Deblocking and deringing filters
    • Efficient temporal coding structures

    In the exercises, we will implement our own image codec (in a gradual manner). We may extend it to a simple video codec.

     

    Suggested reading

    • Bull, D. R., “Communicating Pictures: A Course in Image and Video Coding,” Elsevier, 2014.
    • Ohm, J.-R., “Multimedia Signal Coding and Transmission,” Springer, 2015.
    • Wien, M., “High Efficiency Video Coding — Coding Tools and Specifications,” Springer 2014.
    • Sze, V., Budagavi, M., and Sullivan, G. J. (eds.), “High Efficiency Video Coding (HEVC): Algorithm and Architectures,” Springer, 2014.
    • Wiegand, T. and Schwarz, H., "Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 4, no. 1–2, 2011.
    • Schwarz, H. and Wiegand, T., “Video Coding: Part II of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 10, no. 1–3, 2016.

  • 19331101 Lecture
    Human Centered Data Science (Claudia Müller-Birn)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    [link HCC-Webseite aktuelles Semester]

    Comments

    In recent years, data science has developed rapidly, primarily due to the progress in machine learning. This development has opened up new opportunities in a variety of social, scientific, and technological areas. From the experience of recent years, however, it is becoming increasingly clear that the concentration on purely statistical and numerical aspects in data science fails to capture social nuances or take ethical criteria into account. The research area Human-Centered Data Science closes this gap at the intersection of Human-Computer Interaction (HCI), Computer-Supported Cooperative Work (CSCW), Human Computation, and the statistical and numerical techniques of Data Science.

    Human-Centered Data Science (HCDS) focuses on fundamental principles of data science and its human implications, including research ethics; data privacy; legal frameworks; algorithmic bias, transparency, fairness, and accountability; data provenance, curation, preservation, and reproducibility; user experience design and research for big data; human computation; effective oral, written, and visual scientific communication; and societal impacts of data science.

    At the end of this course, students will understand the main concepts, theories, practices, and different perspectives on which data can be collected and manipulated. Furthermore, students will be able to realize the impact of current technological developments may have on society.

    This course curriculum was initially developed by Jonathan T. Morgan, Cecilia Aragon, Os Keyes, and Brock Craft. We have adapted the curriculum for the European context and our specific understanding of the field.

    Suggested reading

    Aragon, C. M., Hutto, C., Echenique, A., Fiore-Gartland, B., Huang, Y., Kim, J., et al. (2016). Developing a Research Agenda for Human-Centered Data Science. (pp. 529–535). Presented at the CSCW Companion, New York, New York, USA: ACM Press. http://doi.org/10.1145/2818052.2855518

    Baumer, E. P. (2017). Toward human-centered algorithm design:. Big Data & Society, 4(2), 205395171771885. http://doi.org/10.1177/2053951717718854

    Kogan, M., Halfaker, A., Guha, S., Aragon, C., Muller, M., & Geiger, S. (2020, January). Mapping Out Human-Centered Data Science: Methods, Approaches, and Best Practices. In Companion of the 2020 ACM International Conference on Supporting Group Work (pp. 151-156).

  • 19333101 Lecture
    Cybersecurity and AI II: Explainability (Gerhard Wunder)
    Schedule: Mo 12:00-14:00, Di 10:00-12:00, Fr 12:00-14:00 (Class starts on: 2025-04-15)
    Location: 1.3.21 Seminarraum T1 (Arnimallee 14)
    
  • 19333701 Lecture
    Ethics and Epistemology of AI (Christoph Benzmüller)
    Schedule: -
    Location: keine Angabe
    

    Comments

    The course Ethics and Epistemology of AI will be offered again in summer 2025 in cooperation with the TU Berlin (Prof. Sabine Ammon) and U Bamberg. It will bring together an interdisciplinary mix of students from different institutions, including BUA Berlin and Erasmus students.

    Innovative. Experimental. Interdisciplinary.

    More Information: https://www.tu.berlin/en/philtech/study-and-teaching/courses/ethics-and-epistemology-of-ai

    Information for interested students:

    • The course primarily targets masters students with interest in assessing critical aspects of latest artificial intelligence technology and to explore possible solutions and improvements; the course is also part of the Berlin Ethics certificate.
    • Online on-boarding meetings are offered on April 16 (14:15) and April 23 (14:15). The link will be communicated.
    • The course starts immediately after easter with a small pre-exercise to be conducted by each participant individually.
    • Very important is that students then meet for one week in person in Berlin from 28. April to 2. Mai. Participation in this intensive (but also great fun) daily event at TU Berlin is crucial, since it is here where the interdisciplinary and interinstitutional working teams are formed and where the working topics are defined in interaction with the supervisors.
    • After the intensive meeting in Berlin the teams work independently  via the internet; the group typically meets online with their supervisors each Wednesday (early afternoon).
    • Group project presentations are scheduled for June 11; after this date the groups then work on their joint final report.
    • This course is challenging but also fun, and you can expect to build an international network of other students who are interested in assessing critical aspects of AI.

    Contact for administrational questions at TU Berlin: Leon Dirmeier (dirmeier@campus.tu-berlin.de)

  • 19336901 Lecture
    Advanced Data Visualization for Artificial Intelligence (Georges Hattab)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    The lecture on Advanced Data Visualization for Artificial Intelligence is a comprehensive exploration of state-of-the-art techniques and tools to create and validate complex visualizations for communicating data insights and stories, with a specific focus on applications in Natural Language Processing (NLP) and Explainable AI. The lecture will introduce participants to the nested model of visualization, which encompasses four layers: characterizing the task and data, abstracting into operations and data types, designing visual encoding and interaction techniques, and creating algorithms to execute techniques efficiently. This model will serve as a framework for designing and validating data visualizations.
    
    Furthermore, the lecture will delve into the application of data visualization in NLP, emphasizing the visualization of word embeddings and language models to aid in the exploration of semantic relationships between words and the interpretation of language model behavior. In the context of Explainable AI, the focus will be on using visualizations to explain model predictions and feature importance, thereby enhancing the interpretability of AI models. By leveraging the nested model of visualization and focusing on NLP and Explainable AI, the lecture aims to empower participants with the essential skills to design and validate advanced data visualizations tailored to these specific applications, ultimately enabling them to effectively communicate complex data patterns and gain deeper insights from their data.

  • 19302802 Practice seminar
    Practice seminar for Applied Biometrics (Andreas Wolf)
    Schedule: Mo 10:00-12:00 (Class starts on: 2025-04-14)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    
  • 19325302 Practice seminar
    Practice seminar for Cluster Computing (Barry Linnert)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: T9/K44 Rechnerpoolraum (Takustr. 9)
    
  • 19327402 Practice seminar
    Practice seminar for image- und video coding (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    
  • 19331102 Practice seminar
    Practice Session on Human Centered Data Science (Claudia Müller-Birn)
    Schedule: Di 16:00-18:00 (Class starts on: 2025-04-15)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    
  • 19333102 Practice seminar
    Practice seminar for Cybersecurity and AI II (Gerhard Wunder)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-28)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    
  • 19333702 Practice seminar
    Ethics and Epistemology of AI (Christoph Benzmüller)
    Schedule: -
    Location: keine Angabe
    
  • 19336902 Practice seminar
    Ü: Advanced Data Visualization for Artificial Intelligence (Georges Hattab)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

• Special Aspects of Software Development

  0089cA1.30
  • 19336901 Lecture
    Advanced Data Visualization for Artificial Intelligence (Georges Hattab)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

    Comments

    The lecture on Advanced Data Visualization for Artificial Intelligence is a comprehensive exploration of state-of-the-art techniques and tools to create and validate complex visualizations for communicating data insights and stories, with a specific focus on applications in Natural Language Processing (NLP) and Explainable AI. The lecture will introduce participants to the nested model of visualization, which encompasses four layers: characterizing the task and data, abstracting into operations and data types, designing visual encoding and interaction techniques, and creating algorithms to execute techniques efficiently. This model will serve as a framework for designing and validating data visualizations.
    
    Furthermore, the lecture will delve into the application of data visualization in NLP, emphasizing the visualization of word embeddings and language models to aid in the exploration of semantic relationships between words and the interpretation of language model behavior. In the context of Explainable AI, the focus will be on using visualizations to explain model predictions and feature importance, thereby enhancing the interpretability of AI models. By leveraging the nested model of visualization and focusing on NLP and Explainable AI, the lecture aims to empower participants with the essential skills to design and validate advanced data visualizations tailored to these specific applications, ultimately enabling them to effectively communicate complex data patterns and gain deeper insights from their data.

  • 19336902 Practice seminar
    Ü: Advanced Data Visualization for Artificial Intelligence (Georges Hattab)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

• Selected Topics in Applied Computer Science

  0089cA1.31
  • 19326601 Lecture
    Markov Chains (Katinka Wolter)
    Schedule: Di 12:00-14:00, Do 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

    Suggested reading

    William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

  • 19326602 Practice seminar
    Practice seminar for Markov Chains (Justus Purat)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

• Empirical Evaluation in Computer Science

  0089cA1.5
  • 19303401 Lecture
    Empirical Methods in Software Engineering (Lutz Prechelt)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    The course language is German, but the actual slides and practice sheets are in English.

    The exam will be formulated in German, but answers may be given in English, too.

    Homepage: http://www.inf.fu-berlin.de/w/SE/VorlesungEmpirie

    Comments

    Software Engineering is a field of so-high socio-technical complexity that the properties (let alone the usefulness) of proposed methods and tools are not at all obvious. We need to evaluate them empirically.

    This course introduces two different manners in which one can think about this situation and approach evaluations:

    1. A quantitative perspective. This aims at quantified statements about the tools and methods and is based on a positivist epistemological stance and corresponding culture.
    2. A qualitative perspective. This aims at making sense of the things that are going on to create the phenomena that give rise to the quantitative outcomes. This perspective is based on an interpretivist epistemological stance and has a culture that values different things.

    Both perspectives have different strengths and weaknesses and are suitable for different types of research interest. In this course, we will learn to think in both of these perspectives and to appreciate the different benefits they provide. We will learn what it means that a study has high quality: it has high credibility and high relevance. We will train diagnosing the various quality problems that often reduce credibility or relevance.

     

    We will work through the most common research methods and will discuss real examples (interesting published studies) of each, along with their strengths and weaknesses.

    Participants will understand how and when to apply each method and for one of them develop some practical skills by doing so.

    Suggested reading

    • Jacob Cohen: The Earth Is Round (p > .05). American Psychologist 49(12): 997003, 1994. Darrell Huff: How to lie with statistics, Penguin 1991.
    • John C. Knight, Nancy G. Leveson: An Experimental Evaluation of the Assumption of Independence in Multi-Version Programming. IEEE Transactions on Software Engineering 12(1):9609, January 1986.
    • John C. Knight, Nancy G. Leveson: A Reply to the Criticisms of the Knight and Leveson Experiment. Software Engineering Notes 15(1):24-35, January 1990.
    • Audris Mockus, Roy T. Fielding, James D. Herbsleb: Two Case Studies of Open Source Software Development: Apache and Mozilla. ACM Transactions of Software Engineering and Methodology 11(3):309-346, July 2002.
    • Timothy Lethbridge: What Knowledge Is Important to a Software Professional? IEEE Computer 33(5):44-50, May 2000.
    • David A. Scanlan: Structured Flowcharts Outperform Pseudocode: An Experimental Comparison. IEEE Software 6(5):28-36, September 1989.
    • Ben Shneiderman, Richard Mayer, Don McKay, Peter Heller: Experimental investigations of the utility of detailed flowcharts in programming. Commun. ACM 20(6):373-381, 1977.
    • Lutz Prechelt, Barbara Unger-Lamprecht, Michael Philippsen, Walter F. Tichy: Two Controlled Experiments Assessing the Usefulness of Design Pattern Documentation in Program Maintenance. IEEE Transactions on Software Engineering 28(6):595-606, 2002.
    • Lutz Prechelt. An Empirical Comparison of Seven Programming Languages: Computer 33(10):23-29, October 2000.
    • Lutz Prechelt: An empirical comparison of C, C++, Java, Perl, Python, Rexx, and Tcl for a search/string-processing program. Technical Report 2000-5, March 2000.
    • Tom DeMarco, Tim Lister: Programmer performance and the effects of the workplace. Proceedings of the 8th international conference on Software engineering. IEEE Computer Society Press, 268-272, 1985.
    • John L. Henning: SPEC CPU2000: Measuring CPU Performance in the New Millennium. Computer 33(7):28-35, July 2000.
    • Susan Elliot Sim, Steve Easterbrook, Richard C. Holt: Using Benchmarking to Advance Research: A Challenge to Software Engineering. Proceedings of the 25th International Conference on Software Engineering (ICSE'03). 2003.
    • Ellen M. Voorhees, Donna Harman: Overview of the Eighth Text REtrieval Conference (TREC-8).
    • Susan Elliott Sim, Richard C. Holt: The Ramp-Up Problem in Software Projects: A case Study of How Software Immigrants Naturalize. Proceedings of the 20th international conference on Software engineering, April 19-25, 1998, Kyoto, Japan: 361-370.
    • Oliver Laitenberger, Thomas Beil, Thilo Schwinn: An Industrial Case Study to Examine a Non-Traditional Inspection Implementation for Requirements Specifications. Empirical Software Engineering 7(4): 345-374, 2002.
    • Yatin Chawathe, Sylvia Ratnasamy, Lee Breslau, Nick Lanham, Scott Shenker: Making Gnutella-like P2P Systems Scalable. Proceedings of ACM SIGCOMM 2003. April 2003.
    • Stephen G. Eick, Todd L. Graves, Alan F. Karr, J.S. Marron, Audris Mockus: Does Code Decay? Assessing the Evidence from Change Management Data. IEEE Transactions of Software Engineering 27(1):12, 2001.
    • Chris Sauer, D. Ross Jeffrey, Lesley Land, Philip Yetton: The Effectiveness of Software Development Technical Reviews: A Behaviorally Motivated Program of Research. IEEE Transactions on Software Engineering 26(1):14, January 2000.

  • 19303402 Practice seminar
    Practice seminar for Empirical Methods in Software Engineering (Lutz Prechelt)
    Schedule: Mi 08:00-10:00 (Class starts on: 2025-04-16)
    Location: T9/046 Seminarraum (Takustr. 9)
    

• Software Project: Theoretical Computer Science A

  0089cA2.10
  • 19308312 Project Seminar
    Implementation Project: Applications of Algorithms (Mahmoud Elashmawi)
    Schedule: Do 08:30-10:00 (Class starts on: 2025-04-10)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

    Prerequsitions

    Basic knowledge in design and anaylsis of algorithms.

    Suggested reading

    je nach Anwendungsgebiet

• Software Project: Theoretical Computer Science B

  0089cA2.11
  • 19308312 Project Seminar
    Implementation Project: Applications of Algorithms (Mahmoud Elashmawi)
    Schedule: Do 08:30-10:00 (Class starts on: 2025-04-10)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

    Prerequsitions

    Basic knowledge in design and anaylsis of algorithms.

    Suggested reading

    je nach Anwendungsgebiet

• Academic Work in Theoretical Computer Science A

  0089cA2.12
  • 19306711 Seminar
    Seminar on Algorithms (László Kozma)
    Schedule: Do 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-17)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    Advanced topics in algorithm design with a changing focus. The topic is determined in each semester.

    This semester we plan a reading-group-style seminar on recent breakthrough results (2020-2025) in shortest paths algorithms.

    Target audience

    Masters students in computer science and mathematics.

    Recommended prerequisites

    "Advanced algorithms" or a similar class.

    Suggested reading

    Spezialliteratur aus Zeitschriften

  • 19331617 Seminar / Undergraduate Course
    Seminar/Proseminar: Information-theoretical principles of ML (Gerhard Wunder)
    Schedule: Fr 14:00-16:00 (Class starts on: 2025-04-25)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    Recently, artificial intelligence and machine learning (AI/ML) has emerged as a valuable tool in the field of communication and signal processing. It is therefore natural to extend the investigations to the field of physical layer security and privacy. This field is still in its infancy with some very preliminary results on wiretap channel code design, feature extraction of wireless channels and a growing part of contributions to privacy-preserving, distributed AI/ML. This seminar will teach the latest advances and synergies between the broad fields of AI/ML and secure communications.

    Keywords: ML overview, basic tools, universal approximation, deep learning, stochastic gradient, acceleration strategies, deep convolutional networks, feature extraction, classification, mutual information neural network estimation, structured sparsity in convolutional neural networks, matrix decompositions

     

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

• Academic Work in Theoretical Computer Science B

  0089cA2.13
  • 19306711 Seminar
    Seminar on Algorithms (László Kozma)
    Schedule: Do 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-17)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    Advanced topics in algorithm design with a changing focus. The topic is determined in each semester.

    This semester we plan a reading-group-style seminar on recent breakthrough results (2020-2025) in shortest paths algorithms.

    Target audience

    Masters students in computer science and mathematics.

    Recommended prerequisites

    "Advanced algorithms" or a similar class.

    Suggested reading

    Spezialliteratur aus Zeitschriften

  • 19331617 Seminar / Undergraduate Course
    Seminar/Proseminar: Information-theoretical principles of ML (Gerhard Wunder)
    Schedule: Fr 14:00-16:00 (Class starts on: 2025-04-25)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    Recently, artificial intelligence and machine learning (AI/ML) has emerged as a valuable tool in the field of communication and signal processing. It is therefore natural to extend the investigations to the field of physical layer security and privacy. This field is still in its infancy with some very preliminary results on wiretap channel code design, feature extraction of wireless channels and a growing part of contributions to privacy-preserving, distributed AI/ML. This seminar will teach the latest advances and synergies between the broad fields of AI/ML and secure communications.

    Keywords: ML overview, basic tools, universal approximation, deep learning, stochastic gradient, acceleration strategies, deep convolutional networks, feature extraction, classification, mutual information neural network estimation, structured sparsity in convolutional neural networks, matrix decompositions

     

  • 19335011 Seminar
    Seminar: Networks, dynamic models and ML for data integration in the life sciences (Katharina Baum)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Comments

    Research seminar of the group Data Integration in the Life Sciences (DILiS). Also open for seminar participation in the Master's program, online participation possible. Please refer to the current schedule on the whiteboard!

    The seminar offers space for the discussion of advanced and integrative data analysis techniques, in particular presentations and discussion of ongoing or planned research projects, news from conferences, review and discussion of current literature and discussion of possible future teaching formats and content, and presentations, as well as final presentations on theses or project seminars. The seminar language is mostly English. Interested students are welcome to attend and drop in without obligation or present a topic of their own choice of interest to the working group as in a usual seminar. Please note: Individual dates may be canceled or postponed. Please contact me in case of questions (katharina.baum@fu-berlin.de)!

• Current Research Topics in Theoretical Computer Science

  0089cA2.3
  • 19320501 Lecture
    Cryptanalysis of Symmetrical Schemes (Marian Margraf)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: 1.4.03 Seminarraum T2 (Arnimallee 14)
    

    Comments

    The lecture aims at a deeper understanding of cryptographic algorithms, especially which design criteria have to be considered for the development of secure encryption algorithms. For that purpose we will get to know and evaluate different cryptanalytic methods for symmetrical and asymmetrical encryption techniques – e.g. linear and differential cryptanalysis on block ciphers, correlation attacks on stream ciphers and algorithms to solve the factorization problem and the discrete logarithm problem. Weaknesses in the implementation, e.g. to exploit side-channel attacks, will be discussed only peripherally.

  • 19321101 Lecture
    Advanced Data Structures (László Kozma)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A3/ 024 Seminarraum (Arnimallee 3-5)
    

    Comments

    Efficient data structures are important components of all nontrivial algorithms, and are basic building blocks of the modern computing infrastructure. Besides their practical importance, the design and analysis of data structures has revealed a rich mathematical theory. The ultimate theoretical limits of data structures are the subject of deep open questions.

    The topic of this course is the design and analysis of advanced data structures (including both classical and recent results).
    An earlier course with a similar selection of topics can be seen here:
    https://page.mi.fu-berlin.de/lkozma/ds2020

    Familiarity with algorithmic and relevant mathematical concepts is assumed (e.g., the course "Advanced algorithms" or similar as a prerequisite).

     

    Suggested reading

    D. E. Knuth, The Art of Computer Programming, Volume 4A: Combinatorial Algorithms, Part 1. (Addison-Wesley, 2011), xv+883pp. ISBN 0-201-03804-8

  • 19322701 Lecture
    Cryptoanalysis of Asymmetrical Schemes (Marian Margraf)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-17)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    Cryptoanalysis of asymmetrical schemes

    The lecture deals with different asymmetrical cryptanalytics, in particular with the supposed hard problems of these processes. Some of the contents are

    • RSA and the problem of factorization
    • DSA and the discrete logarithm problem
    • Merkel-Hellman and the knapsack and grid problem
    • McEliece and the problem of decoding
    • Matsumoto-Imai and the multivariate Polynomial System

    Knowledge in the areas of IT security and cryptography is obligatory.

  • 19337401 Lecture
    Elliptic Curve Cryptography (Marian Margraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19321102 Practice seminar
    Practice seminar for Advanced Data Structures (N.N.)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: A3/019 Seminarraum (Arnimallee 3-5)
    

    Comments

    Übungen

  • 19322702 Practice seminar
    Practice seminar for Cryptoanalysis of Asymmetrical Schemes (Marian Margraf)
    Schedule: Mi 16:00-18:00 (Class starts on: 2025-04-16)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    
  • 19337402 Practice seminar
    Tutorials for Elliptic Curve Cryptography (Marian Margraf)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-04-17)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

• Computational Geometry

  0089cA2.4
  • 19313801 Lecture
    Computational Geometry (Günther Rothe)
    Schedule: Mo 10:00-12:00, Do 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/051 Seminarraum (Takustr. 9)
    
  • 19313802 Practice seminar
    Practice seminar for Computational Geometry (Günther Rothe)
    Schedule: Fr 14:00-16:00 (Class starts on: 2025-04-25)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

• Selected Topics in Theoretical Computer Science

  0089cA2.5
  • 19315401 Lecture
    Multiplicative Weights - A Popular Algorithmic Technique with Countless Applications (Wolfgang Mulzer)
    Schedule: Di 14:00-16:00, Fr 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Comments

    Just like greedy algorithms, dynamic programming, or divide-and-conquer, the multiplicative weights method is a fundamental algorithmic technique with countless applications across disciplines. However, it is taught only rarely in basic classes.

    
    
    

    In this class, we will study the multiplicative weights method in detail. We will learn about the basic technique and its variations, explore connections to other fields such as online convex optimization and machine learning, and see the beautiful mathematics that lies behind it.

    
    
    

    We will also see many applications of the technique, with examples from combinatorial optimization, machine learning, algorithmic game theory, computational geometry, information theory, online algorithms, and many more. For some of the applications, we will have invited speakers who have applied the technique in their respective fields.

    
    
    

    The class is jointly attended by students at Sorbonne Paris Nord in Paris and will be given in a hybrid format.

    
    
    

    The course website can be found here: https://www.inf.fu-berlin.de/lehre/SS25/mwu/

    
    

    Suggested reading

    Wird noch bekannt gegeben.

  • 19326601 Lecture
    Markov Chains (Katinka Wolter)
    Schedule: Di 12:00-14:00, Do 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

    Suggested reading

    William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

  • 19315402 Practice seminar
    Practice seminar for Multiplicative Weights (Michaela Krüger)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    
  • 19326602 Practice seminar
    Practice seminar for Markov Chains (Justus Purat)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

• Advanced topics in Theoretical Computer Science

  0089cA2.6
  • 19315401 Lecture
    Multiplicative Weights - A Popular Algorithmic Technique with Countless Applications (Wolfgang Mulzer)
    Schedule: Di 14:00-16:00, Fr 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Comments

    Just like greedy algorithms, dynamic programming, or divide-and-conquer, the multiplicative weights method is a fundamental algorithmic technique with countless applications across disciplines. However, it is taught only rarely in basic classes.

    
    
    

    In this class, we will study the multiplicative weights method in detail. We will learn about the basic technique and its variations, explore connections to other fields such as online convex optimization and machine learning, and see the beautiful mathematics that lies behind it.

    
    
    

    We will also see many applications of the technique, with examples from combinatorial optimization, machine learning, algorithmic game theory, computational geometry, information theory, online algorithms, and many more. For some of the applications, we will have invited speakers who have applied the technique in their respective fields.

    
    
    

    The class is jointly attended by students at Sorbonne Paris Nord in Paris and will be given in a hybrid format.

    
    
    

    The course website can be found here: https://www.inf.fu-berlin.de/lehre/SS25/mwu/

    
    

    Suggested reading

    Wird noch bekannt gegeben.

  • 19326601 Lecture
    Markov Chains (Katinka Wolter)
    Schedule: Di 12:00-14:00, Do 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Comments

    In this course we will study stochastic models commonly used to analyse the performance of dynamic systems. Markov models and queues are used to study the behaviour over time of a wide range of systems, from computer hardware, communication systems, biological systems, epidemics, traffic networks to crypto-currencies. We will take a tour of the basics of Markov modelling, starting from birth-death processes, the Poisson process to general Markov and semi-Markov processes and solution methods for those processes. Then we will look at queueing models and queueing networks with exact and approximate solution algorithms. If time allows we will finally study some of the foundations of discrete event simulation.

    Suggested reading

    William Stewart. Probability, Markov Chains, Queues and Simulation. Princeton University Press 2009.

  • 19315402 Practice seminar
    Practice seminar for Multiplicative Weights (Michaela Krüger)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: A7/SR 140 Seminarraum (Hinterhaus) (Arnimallee 7)
    
  • 19326602 Practice seminar
    Practice seminar for Markov Chains (Justus Purat)
    Schedule: Di 14:00-16:00 (Class starts on: 2025-04-15)
    Location: A6/SR 007/008 Seminarraum (Arnimallee 6)
    

• Special aspects of Theoretical Computer Science

  0089cA2.7
  • 19320501 Lecture
    Cryptanalysis of Symmetrical Schemes (Marian Margraf)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: 1.4.03 Seminarraum T2 (Arnimallee 14)
    

    Comments

    The lecture aims at a deeper understanding of cryptographic algorithms, especially which design criteria have to be considered for the development of secure encryption algorithms. For that purpose we will get to know and evaluate different cryptanalytic methods for symmetrical and asymmetrical encryption techniques – e.g. linear and differential cryptanalysis on block ciphers, correlation attacks on stream ciphers and algorithms to solve the factorization problem and the discrete logarithm problem. Weaknesses in the implementation, e.g. to exploit side-channel attacks, will be discussed only peripherally.

  • 19321101 Lecture
    Advanced Data Structures (László Kozma)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A3/ 024 Seminarraum (Arnimallee 3-5)
    

    Comments

    Efficient data structures are important components of all nontrivial algorithms, and are basic building blocks of the modern computing infrastructure. Besides their practical importance, the design and analysis of data structures has revealed a rich mathematical theory. The ultimate theoretical limits of data structures are the subject of deep open questions.

    The topic of this course is the design and analysis of advanced data structures (including both classical and recent results).
    An earlier course with a similar selection of topics can be seen here:
    https://page.mi.fu-berlin.de/lkozma/ds2020

    Familiarity with algorithmic and relevant mathematical concepts is assumed (e.g., the course "Advanced algorithms" or similar as a prerequisite).

     

    Suggested reading

    D. E. Knuth, The Art of Computer Programming, Volume 4A: Combinatorial Algorithms, Part 1. (Addison-Wesley, 2011), xv+883pp. ISBN 0-201-03804-8

  • 19322701 Lecture
    Cryptoanalysis of Asymmetrical Schemes (Marian Margraf)
    Schedule: Do 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-17)
    Location: A6/SR 032 Seminarraum (Arnimallee 6)
    

    Comments

    Cryptoanalysis of asymmetrical schemes

    The lecture deals with different asymmetrical cryptanalytics, in particular with the supposed hard problems of these processes. Some of the contents are

    • RSA and the problem of factorization
    • DSA and the discrete logarithm problem
    • Merkel-Hellman and the knapsack and grid problem
    • McEliece and the problem of decoding
    • Matsumoto-Imai and the multivariate Polynomial System

    Knowledge in the areas of IT security and cryptography is obligatory.

  • 19337401 Lecture
    Elliptic Curve Cryptography (Marian Margraf)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19320502 Practice seminar
    Practice seminar for Cryptanalysis (Marian Margraf)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    
  • 19321102 Practice seminar
    Practice seminar for Advanced Data Structures (N.N.)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: A3/019 Seminarraum (Arnimallee 3-5)
    

    Comments

    Übungen

  • 19322702 Practice seminar
    Practice seminar for Cryptoanalysis of Asymmetrical Schemes (Marian Margraf)
    Schedule: Mi 16:00-18:00 (Class starts on: 2025-04-16)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    
  • 19337402 Practice seminar
    Tutorials for Elliptic Curve Cryptography (Marian Margraf)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-04-17)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

• Current Research Topics in Computer Systems

  0089cA3.10
  • 19325301 Lecture
    Cluster Computing (Barry Linnert)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    • Computer Science Master students

    Requirements

    • Experience with computers and software as well as programing skills.

    Language

    • The course language is German (or English if requested).
    • The exam will be formulated in German, but answers may be given in English, too.

    Credits & Exams

    The criteria for gaining credits are

    • active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
    • passing of the exam

    Website

    https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

     

    Comments

    Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented.

    Suggested reading

    • Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
    • Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
    • Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
    • Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
    • Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

  • 19327401 Lecture
    Image- and video coding (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    This course introduces the most important concepts and algorithms that are used in modern image and video coding approaches. We will particularly focus on techniques that are found in current international video coding standards.

    In a short first part, we introduce the so-called raw data formats, which are used as input and output formats of image and video codecs. This part covers the following topics:

    • Colour spaces and their relation to human visual perception
    • Transfer functions (gamma encoding)
    • Why do we use the YCbCr format?

    The second part of the course deals with still image coding and includes the following topics:

    • The start: How does JPEG work?
    • Why do we use the Discrete Cosine Transform?
    • Efficient coding of transform coefficients
    • Prediction of image blocks
    • Adaptive block partitioning
    • How do we take decisions in an encoder?
    • Optimized quantization

    In the third part, we discuss approaches that make video coding much more efficient than coding all pictures using still image coding techniques:

    • Motion-compensated prediction
    • Coding of motion vectors
    • Algorithms for motion estimation
    • Sub-sample accurate motion vectors and interpolation filters
    • Usage of multiple reference pictures
    • What are B pictures and why do we use them?
    • Deblocking and deringing filters
    • Efficient temporal coding structures

    In the exercises, we will implement our own image codec (in a gradual manner). We may extend it to a simple video codec.

     

    Suggested reading

    • Bull, D. R., “Communicating Pictures: A Course in Image and Video Coding,” Elsevier, 2014.
    • Ohm, J.-R., “Multimedia Signal Coding and Transmission,” Springer, 2015.
    • Wien, M., “High Efficiency Video Coding — Coding Tools and Specifications,” Springer 2014.
    • Sze, V., Budagavi, M., and Sullivan, G. J. (eds.), “High Efficiency Video Coding (HEVC): Algorithm and Architectures,” Springer, 2014.
    • Wiegand, T. and Schwarz, H., "Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 4, no. 1–2, 2011.
    • Schwarz, H. and Wiegand, T., “Video Coding: Part II of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 10, no. 1–3, 2016.

  • 19325302 Practice seminar
    Practice seminar for Cluster Computing (Barry Linnert)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: T9/K44 Rechnerpoolraum (Takustr. 9)
    
  • 19327402 Practice seminar
    Practice seminar for image- und video coding (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

• Special Aspects of Computer Systems

  0089cA3.11
  • 19325301 Lecture
    Cluster Computing (Barry Linnert)
    Schedule: Di 10:00-12:00 (Class starts on: 2025-04-15)
    Location: T9/055 Seminarraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    • Computer Science Master students

    Requirements

    • Experience with computers and software as well as programing skills.

    Language

    • The course language is German (or English if requested).
    • The exam will be formulated in German, but answers may be given in English, too.

    Credits & Exams

    The criteria for gaining credits are

    • active participation in the tutorials: regular preparation of assignements & presentation of results in the tutorials
    • passing of the exam

    Website

    https://www.mi.fu-berlin.de/w/SE/VorlesungClusterComputing

     

    Comments

    Cluster computer are the prevailing type of high performance computers. They are built of custom off-the-shelf processor boards that are connected by a high speed interconnection network. Although usually locally integrated, they are conceptually distributed systems with local operating system images. Their enormous potential, however, can only be exploited, if program code and data are optimally distributed across the nodes. Cluster management mechanisms also need to be scalable to be employed in systems with thousands of nodes. The lecture course gives an overview of the architecture of cluster computers and the related management problems for which algorithmic solutions are presented.

    Suggested reading

    • Heiss, H.-U.: Prozessorzuteilung in Parallelrechnern, BI-Verlag, Mannheim, 1996
    • Andrews, G. A.: Foundations of Multithreaded, Parallel and Distributed Programming, Addison-Wesley, 2000
    • Pfister, G.: In Search of Clusters 2nd ed., Prentice Hall, 1998
    • Zomaya, A.: Parallel and distributed computing handbook, McGraw Gill, 1995
    • Buyya, R.: High Performance Cluster Computing, Vol. 1+2, Prentice Hall, 1999

  • 19327401 Lecture
    Image- and video coding (Heiko Schwarz)
    Schedule: Mo 14:00-16:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    This course introduces the most important concepts and algorithms that are used in modern image and video coding approaches. We will particularly focus on techniques that are found in current international video coding standards.

    In a short first part, we introduce the so-called raw data formats, which are used as input and output formats of image and video codecs. This part covers the following topics:

    • Colour spaces and their relation to human visual perception
    • Transfer functions (gamma encoding)
    • Why do we use the YCbCr format?

    The second part of the course deals with still image coding and includes the following topics:

    • The start: How does JPEG work?
    • Why do we use the Discrete Cosine Transform?
    • Efficient coding of transform coefficients
    • Prediction of image blocks
    • Adaptive block partitioning
    • How do we take decisions in an encoder?
    • Optimized quantization

    In the third part, we discuss approaches that make video coding much more efficient than coding all pictures using still image coding techniques:

    • Motion-compensated prediction
    • Coding of motion vectors
    • Algorithms for motion estimation
    • Sub-sample accurate motion vectors and interpolation filters
    • Usage of multiple reference pictures
    • What are B pictures and why do we use them?
    • Deblocking and deringing filters
    • Efficient temporal coding structures

    In the exercises, we will implement our own image codec (in a gradual manner). We may extend it to a simple video codec.

     

    Suggested reading

    • Bull, D. R., “Communicating Pictures: A Course in Image and Video Coding,” Elsevier, 2014.
    • Ohm, J.-R., “Multimedia Signal Coding and Transmission,” Springer, 2015.
    • Wien, M., “High Efficiency Video Coding — Coding Tools and Specifications,” Springer 2014.
    • Sze, V., Budagavi, M., and Sullivan, G. J. (eds.), “High Efficiency Video Coding (HEVC): Algorithm and Architectures,” Springer, 2014.
    • Wiegand, T. and Schwarz, H., "Source Coding: Part I of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 4, no. 1–2, 2011.
    • Schwarz, H. and Wiegand, T., “Video Coding: Part II of Fundamentals of Source and Video Coding,” Foundations and Trends in Signal Processing, Now Publishers, vol. 10, no. 1–3, 2016.

  • 19325302 Practice seminar
    Practice seminar for Cluster Computing (Barry Linnert)
    Schedule: Do 10:00-12:00 (Class starts on: 2025-04-17)
    Location: T9/K44 Rechnerpoolraum (Takustr. 9)
    
  • 19327402 Practice seminar
    Practice seminar for image- und video coding (Heiko Schwarz)
    Schedule: Mo 12:00-14:00 (Class starts on: 2025-04-14)
    Location: T9/053 Seminarraum (Takustr. 9)
    

• Microprocessor Lab

  0089cA3.2
  • 19310030 Internship
    Practical Project: Microprocessors (Larissa Groth)
    Schedule: Mo 16:00-18:00, Di 14:00-16:00, Mi 12:00-14:00 (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Additional information / Pre-requisites

    Important information about the course:
    The microprocessor practical course will be offered this semester with a joint theory session on Wednesdays, 12-14 o'clock, and two independent practical exercise sessions:

    • Group A, Mondays, 4-6 p.m. Takustraße 9, Room K63
    • Group B, Tuesdays, 2-4 p.m. Takustraße 9, Room K63

    One of these practice dates must be chosen.

    Comments

    ATTENTION: Contrary to the schedule in the course catalog, this course does not have 3 mandatory dates, but only 2! See below for further information!

    The overwhelming majority of future computer systems will be characterized by communicating, embedded systems. These are found in machine controls, household appliances, motor vehicles, airplanes, intelligent buildings, etc. and will in future be increasingly integrated into networks such as the Internet.

    The internship will address the architecture of embedded systems and demonstrate the differences to traditional PC architectures (e.g., real-time capability, interaction with the environment) with practical examples. The internship is based on 16- and 32-bit microcontroller systems.

    The main focus of the internship is the following:

        register structures
        memory organization
        Hardware assembler and high-language programming
        I / O system and timer programming
        Interrupt system
        Watchdog logic
        Analog interface
        Bus system connection of components
        Communication (serial, CAN bus, Ethernet, radio and USB)
        Control of models and use of different sensors

    Suggested reading

    • Brian W. Kernighan, Dennis M. Ritchie: The C Programming Language, Second Edition, Prentice Hall, 1988.

• Mobile Communications

  0089cA3.3
  • 19303901 Lecture
    Mobile Communications (Jochen Schiller)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: T9/049 Seminarraum (Takustr. 9)
    

    Comments

    The module mobile communication presents major topics from mobile and wireless communications - the key drivers behind today's communication industry that influence everybody's daily life. 

    The whole lecture focuses on a system perspective giving many pointers to real systems, standardization and current research.

    The format of the lecture is the flipped classroom, i.e., you should watch the videos of a lecture BEFORE participating in the Q&A session. We will then discuss all open issues, answer questions etc. during the Q&A session.

    Main topics of the lecture are:

    • Basics of wireless transmission: frequencies, signals, antennas, multiplexing, modulation, spread spectrum
    • Medium access: SDMA, FDMA, TDMA, CDMA;
    • Wireless telecommunication systems: GSM, TETRA, IMT-2000, LTE, 5G
    • Wireless local area networks: infrastructure/ad-hoc, IEEE 802.11/15, Bluetooth, ZigBee
    • Mobile networking: Mobile IP, ad-hoc networks
    • Mobile transport layer: traditional TCP, additional mechanisms
    • Outlook: 5 to 6G, low power wireless networks

    Suggested reading

    Jochen Schiller, Mobilkommunikation, Addison-Wesley, 2.Auflage 2003

    Alle Unterlagen verfügbar unter http://www.mi.fu-berlin.de/inf/groups/ag-tech/teaching/resources/Mobile_Communications/course_Material/index.html

• Robotics

  0089cA3.4
  • 19304701 Lecture
    Robotics (Daniel Göhring)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-04-16)
    Location: T9/Gr. Hörsaal (Takustr. 9)
    

    Additional information / Pre-requisites

    Students interested in robotics with application to autonomous vehicles. Voraussetzungen: As a prerequisite, student should have basic knowledge of maths, in particular linear algebra and a bit of optimization. Students will work with a real model car in the robotics lab.

    Comments

    Content

    This class will give an introduction to robotics. It will be structured into the following parts:

    • Generating motion and and dynamic control: This chapter will cover coordinate frames, non-holonomic constraints, Ackermann-drive (in analogy to street cars), PID.
    • Planning: Planning around obstacles, path finding, Dijkstra, A*, configuration space obstacles, RRTs, lattice planners, gradient methods, potential fields, splines.
    • Localization and mapping: state estimation problem, Bayesian filter, Odometry, Particle & Kalman filter, Extended and Unscented Kalman-Filter, simultaneous localization and mapping (SLAM).
    • Vision and perception: SIFT, HOG-features, Deformable parts models, hough transform, lane detection, 3d-point clouds, RANSAC .

    After these lectures, students will be able to design basic algorithms for motion, control and state estimation for robotics.

    The lecture will be in German, accompanying materials in English.

    Suggested reading

    Literatur:

    
    John J Craig: Introduction to Robotics: Mechanics and Control; Steven LaValle: Planning Algorithms; Sebastian Thrun, Wolfram Burgard, Dieter Fox: Probabilistic Robotics
    
     

  • 19304702 Practice seminar
    Practice seminar for Robotics (Daniel Göhring)
    Schedule: Do 12:00-14:00 (Class starts on: 2025-04-17)
    Location: T9/049 Seminarraum (Takustr. 9)
    

• Software Project: Computer Systems A

  0089cA3.6
  • 19315312 Project Seminar
    Software Project: Distributed Systems (Justus Purat)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-04-16)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    
  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Software Project: Computer Systems B

  0089cA3.7
  • 19315312 Project Seminar
    Software Project: Distributed Systems (Justus Purat)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-04-16)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    
  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Academic Work in Computer Systems A

  0089cA3.8
  • 19307117 Seminar / Undergraduate Course
    Seminar/Proseminar: Smart Homes and the World of IoT (Marius Max Wawerek)
    Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    This seminar focuses on various aspects of modern “Internet of Things” (IoT) systems. The main component will be applications and publications related to the area of the “Smart Home”. At the beginning of the seminar, suggested topics will be given, which will mainly deal with data analysis (both “normal” statistics and machine learning), security aspects and the usefulness of the Internet of Things or the “Smart Home”. You are also welcome to suggest your own topics, but they must be related to IoT systems. The topics should be worked on alone.

    About the procedure: This seminar takes place throughout the semester. There are few meetings, but these are mandatory. On the first date (14.04.2025) the list of topics will be handed out and discussed. In the next week (21.04.2025) there will be another opportunity to discuss topic suggestions. If you are interested in your own topic, please prepare a short (2-3 minutes) outline of your proposal. As in the third week (28.04.2025) the topics will be assigned.

    
    There will then be 3 presentation dates per person: the presentation of the literature research (19.05.2025), a short interim presentation (16.06.2025) and the final presentation on one of the dates in the period from 30.06.2025 - 14.07.2025. There will be no further meetings beyond this.

    This means that, depending on the number of participants, the following meetings are mandatory:

    • 14.04.2025
    • 21.04.2025
    • 19.05.2025
    • 16.06.2025
    • 30.06.2025
    • 07.07.2025
    • 14.07.2025

  • 19310817 Seminar / Undergraduate Course
    Seminar/Proseminar: High Performance and Cloud Computing (Barry Linnert)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-22)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    When it comes to processing complex applications or large amounts of data within a reasonable time frame, the use of parallel programs is unavoidable. However, these can be very different due to the specific application framework or the technical environments. For example, high-performance computing (HPC) uses supercomputers that support applications with a high degree of interaction, while cloud computing focuses on the provision of data and computing capacity on demand.
    Both application areas have challenges both at the programming level and in the administration of the corresponding systems.
    In the seminar, we will focus on one aspect of this spectrum and summarize and evaluate current research in this area.

    Further information on the procedure will be provided at the first meeting on 22.04.2025.

  • 19329617 Seminar / Undergraduate Course
    Seminar/Proseminar: Telematics (Jochen Schiller)
    Schedule: Di 15.07. 10:00-16:00, Di 22.07. 10:00-18:00 (Class starts on: 2025-07-15)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    This seminar focuses on several aspects of technical Computer Science. At the start of the seminar you will receive a list of suggested topics that mainly deal with particular aspects of the so-called Trusted Computing and security issues in the Internet of Things. You are also very welcome to suggest your own research topic that is closely related to technical Computer Science. You can work on your topic exclusively or in a small group of 2-3 students. But then, it has to be apparent who contributed what part to the seminar paper.

     

    It is possible to combine this seminar with the software project Telematics. Then, the theoretical foundations of the topic are dealt with in the scientific seminar paper and implemented in practice in the software project. Please note that the seminar paper is not supposed to deal with details of the implementation and that you are still obliged to write an accurate documentation of the software project in written form. 

     

    Concerning the schedule: This seminar takes place during the semester. There are only a few meetings, but these are mandatory. On the first meeting (03.11.2020), the topic list will be handed out and discussed. Please prepare a short (2-3 minutes) overview of your own topic suggestion if you would like to include it in the seminar. On the next week (10.11.2020), the topics will be assigned. After that there will be 3 presentation dates in total: the topic presentation (01.12.2021), a short interim presentation (12.01.2021) and the final presentation (23.02.2021). There will be no further meetings beyond that. This semester, all meetings will take place as video conferences with Webex.

• Academic Work in Computer Systems B

  0089cA3.9
  • 19307117 Seminar / Undergraduate Course
    Seminar/Proseminar: Smart Homes and the World of IoT (Marius Max Wawerek)
    Schedule: Mo 14:00-16:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    This seminar focuses on various aspects of modern “Internet of Things” (IoT) systems. The main component will be applications and publications related to the area of the “Smart Home”. At the beginning of the seminar, suggested topics will be given, which will mainly deal with data analysis (both “normal” statistics and machine learning), security aspects and the usefulness of the Internet of Things or the “Smart Home”. You are also welcome to suggest your own topics, but they must be related to IoT systems. The topics should be worked on alone.

    About the procedure: This seminar takes place throughout the semester. There are few meetings, but these are mandatory. On the first date (14.04.2025) the list of topics will be handed out and discussed. In the next week (21.04.2025) there will be another opportunity to discuss topic suggestions. If you are interested in your own topic, please prepare a short (2-3 minutes) outline of your proposal. As in the third week (28.04.2025) the topics will be assigned.

    
    There will then be 3 presentation dates per person: the presentation of the literature research (19.05.2025), a short interim presentation (16.06.2025) and the final presentation on one of the dates in the period from 30.06.2025 - 14.07.2025. There will be no further meetings beyond this.

    This means that, depending on the number of participants, the following meetings are mandatory:

    • 14.04.2025
    • 21.04.2025
    • 19.05.2025
    • 16.06.2025
    • 30.06.2025
    • 07.07.2025
    • 14.07.2025

  • 19310817 Seminar / Undergraduate Course
    Seminar/Proseminar: High Performance and Cloud Computing (Barry Linnert)
    Schedule: Di 12:00-14:00 (Class starts on: 2025-04-22)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    When it comes to processing complex applications or large amounts of data within a reasonable time frame, the use of parallel programs is unavoidable. However, these can be very different due to the specific application framework or the technical environments. For example, high-performance computing (HPC) uses supercomputers that support applications with a high degree of interaction, while cloud computing focuses on the provision of data and computing capacity on demand.
    Both application areas have challenges both at the programming level and in the administration of the corresponding systems.
    In the seminar, we will focus on one aspect of this spectrum and summarize and evaluate current research in this area.

    Further information on the procedure will be provided at the first meeting on 22.04.2025.

  • 19329617 Seminar / Undergraduate Course
    Seminar/Proseminar: Telematics (Jochen Schiller)
    Schedule: Di 15.07. 10:00-16:00, Di 22.07. 10:00-18:00 (Class starts on: 2025-07-15)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    This seminar focuses on several aspects of technical Computer Science. At the start of the seminar you will receive a list of suggested topics that mainly deal with particular aspects of the so-called Trusted Computing and security issues in the Internet of Things. You are also very welcome to suggest your own research topic that is closely related to technical Computer Science. You can work on your topic exclusively or in a small group of 2-3 students. But then, it has to be apparent who contributed what part to the seminar paper.

     

    It is possible to combine this seminar with the software project Telematics. Then, the theoretical foundations of the topic are dealt with in the scientific seminar paper and implemented in practice in the software project. Please note that the seminar paper is not supposed to deal with details of the implementation and that you are still obliged to write an accurate documentation of the software project in written form. 

     

    Concerning the schedule: This seminar takes place during the semester. There are only a few meetings, but these are mandatory. On the first meeting (03.11.2020), the topic list will be handed out and discussed. Please prepare a short (2-3 minutes) overview of your own topic suggestion if you would like to include it in the seminar. On the next week (10.11.2020), the topics will be assigned. After that there will be 3 presentation dates in total: the topic presentation (01.12.2021), a short interim presentation (12.01.2021) and the final presentation (23.02.2021). There will be no further meetings beyond that. This semester, all meetings will take place as video conferences with Webex.

• Software project A

  0159cA1.1
  • 19308312 Project Seminar
    Implementation Project: Applications of Algorithms (Mahmoud Elashmawi)
    Schedule: Do 08:30-10:00 (Class starts on: 2025-04-10)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

    Prerequsitions

    Basic knowledge in design and anaylsis of algorithms.

    Suggested reading

    je nach Anwendungsgebiet

  • 19308412 Project Seminar
    Software Project: Data Management (Agnès Voisard)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-05)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students in the Master's or Bachelor's programme

     

    Prerequisites

    Good programming skills, introduction to database systems.

    Comments

    Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Corporate Semantic Web

    Further information can be found on the course website

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

    Suggested reading

    Corporate Semantic Web

  • 19315312 Project Seminar
    Software Project: Distributed Systems (Justus Purat)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-04-16)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    
  • 19323612 Project Seminar
    The AMOS Project (Lutz Prechelt)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Educational objectives and competencies

    • Students learn about software products and software development in an industry context
    • Students learn about agile methods, in particular Scrum and Extreme Programming
    • Students learn about open source software development and its underlying principles
    • Students gain practical hands-on experience with a Scrum process and XP technical practices

    Target group

    Students of computer science (and related fields). If you want to play the software developer role, you should have had practical programming experience. This is not a course to learn programming.

    Language

    English (lectures in English, team meeting German or English by choice of student team)

    Grading

    • Software developer
      • 10% of grade: 5 class quizzes, each consisting of 5 questions at 2 points each
      • 90% of grade: Weekly project work

    Other

    • SWS: 4 SWS (2 SWS lecture, 2 SWS team meeting)
    • Semester: Every semester
    • Modality: Online, across multiple universities
    • Tags: Scrum

     

    Comments

    This course teaches agile methods (Scrum and XP) and open source tools using a single semester-long project. It takes place online and across multiple universities. Topics covered are:

    • Agile methods and related software development processes
    • Scrum roles, process practices, including product and engineering management
    • Technical practices like refactoring, continuous integration, and test-driven development
    • Principles and best practices of open source software development

    The project is a software development project in which each student team works with an industry partner who provides the idea for the project. This is a practical hands-on experience.

    Students play the role of a software developer. In this role, students estimate the effort for requirements and implement them. Students must have prior software development experience.

    Students will be organized into teams of 7-9 people, combining one Scrum master with two product owners with six software developers.

    An industry partner will provide requirements to be worked out in detail by the product owners and to be realized by the software developers. The available projects will be presented in the run-up to the course.

    Class consists of a 90 min. lecture followed by a 90 min. team meeting. Rooms and times for team meetings are assigned at the beginning of the semester. You must be able to regularly participate in the team meetings. If you can't, do not sign up for this course.

    Attention: this course is organized externally and additional sign-up steps are required. Sign-up and further course information are available through a Google spreadsheet at https://amos.uni1.de – please declare your interest by filling out the course interest declaration survey as soon as it opens.

    Suggested reading

    http://goo.gl/5Wqnr7

  • 19329912 Project Seminar
    Software Project: Secure Identity (Volker Roth)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Comments

    Die Aufgabe wird die Entwicklung einer Software sein. Es wird um sichere Softwareentwicklung gehen. Die Aufgabe wird in Gruppenarbeit gelöst.

  • 19334212 Project Seminar
    Softwareproject: Machine Learning and Explainability for Improved (Cancer) Treatment (Pauline Hiort)
    Schedule: Di 15:00-17:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-26)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    In the software project, we will implement, train, and evaluate various machine learning (ML) methods. The focus of the project is on neural networks (NN) and their explainability. We will compare the methods with different baseline models, such as regression models. The various ML methods will be applied to a specific dataset, e.g., for predicting drug combinations for cancer treatment, and evaluated accordingly. The dataset will be prepared by us and analyzed using the implemented methods. Additionally, we will focus on explainability to ensure that the predictions of the ML models are understandable and interpretable. For this purpose, we will integrate appropriate explainability techniques to better understand and visualize the decision-making processes of the models.

    The programming language is Python, and we plan to use modern Python modules for ML like scikit-learn, and PyTorch. Good Python skills are required. The goal is to create a Python package that provides reusable code for preprocessing, training ML models, and evaluating results with documentation (e.g., using Sphinx) for the specific use case. The software project takes place throughout the semester and can also be conducted in English.

  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Software project B

  0159cA1.2
  • 19308312 Project Seminar
    Implementation Project: Applications of Algorithms (Mahmoud Elashmawi)
    Schedule: Do 08:30-10:00 (Class starts on: 2025-04-10)
    Location: T9/053 Seminarraum (Takustr. 9)
    

    Comments

    Contents

    We choose a typical application area of algorithms, usually for geometric problems, and develop software solutions for it, e.g., computer graphics (representation of objects in a computer, projections, hidden edge and surface removal, lighting, raytracing), computer vision (image processing, filtering, projections, camera calibration, stereo-vision) or pattern recognition (classification, searching).

    Prerequsitions

    Basic knowledge in design and anaylsis of algorithms.

    Suggested reading

    je nach Anwendungsgebiet

  • 19308412 Project Seminar
    Software Project: Data Management (Agnès Voisard)
    Schedule: Mo 12:00-14:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-05)
    Location: T9/137 Konferenzraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group

    Students in the Master's or Bachelor's programme

     

    Prerequisites

    Good programming skills, introduction to database systems.

    Comments

    Subject of the project: either development of software together with a company (in this case: 4­ weeks fulltime August/September) or we build a so called NoSQL system. Decision in March. Further information are published in the KVV.

    Suggested reading

    Wird bekannt gegeben. / To be announced.

  • 19314012 Project Seminar
    Software Project: Semantic Technologies (Adrian Paschke)
    Schedule: Mi 14:00-16:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Additional information / Pre-requisites

    Corporate Semantic Web

    Further information can be found on the course website

    Comments

    Mixed groups of master and bachelor students will either implement an independent project or are part of a larger project in the area of semantic technologies. They will gain in-depth programming knowledge about applications of semantic technologies and artificial intelligence techniques in the Corporate Semantic Web. They will practice teamwork and best practices in software development of large distributed systems and Semantic Web applications. The software project can be done in collaboration with an external partner from industry or standardization. It is possible to continue the project as bachelor or master thesis.

    Suggested reading

    Corporate Semantic Web

  • 19315312 Project Seminar
    Software Project: Distributed Systems (Justus Purat)
    Schedule: Mi 12:00-14:00 (Class starts on: 2025-04-16)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    
  • 19323612 Project Seminar
    The AMOS Project (Lutz Prechelt)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Educational objectives and competencies

    • Students learn about software products and software development in an industry context
    • Students learn about agile methods, in particular Scrum and Extreme Programming
    • Students learn about open source software development and its underlying principles
    • Students gain practical hands-on experience with a Scrum process and XP technical practices

    Target group

    Students of computer science (and related fields). If you want to play the software developer role, you should have had practical programming experience. This is not a course to learn programming.

    Language

    English (lectures in English, team meeting German or English by choice of student team)

    Grading

    • Software developer
      • 10% of grade: 5 class quizzes, each consisting of 5 questions at 2 points each
      • 90% of grade: Weekly project work

    Other

    • SWS: 4 SWS (2 SWS lecture, 2 SWS team meeting)
    • Semester: Every semester
    • Modality: Online, across multiple universities
    • Tags: Scrum

     

    Comments

    This course teaches agile methods (Scrum and XP) and open source tools using a single semester-long project. It takes place online and across multiple universities. Topics covered are:

    • Agile methods and related software development processes
    • Scrum roles, process practices, including product and engineering management
    • Technical practices like refactoring, continuous integration, and test-driven development
    • Principles and best practices of open source software development

    The project is a software development project in which each student team works with an industry partner who provides the idea for the project. This is a practical hands-on experience.

    Students play the role of a software developer. In this role, students estimate the effort for requirements and implement them. Students must have prior software development experience.

    Students will be organized into teams of 7-9 people, combining one Scrum master with two product owners with six software developers.

    An industry partner will provide requirements to be worked out in detail by the product owners and to be realized by the software developers. The available projects will be presented in the run-up to the course.

    Class consists of a 90 min. lecture followed by a 90 min. team meeting. Rooms and times for team meetings are assigned at the beginning of the semester. You must be able to regularly participate in the team meetings. If you can't, do not sign up for this course.

    Attention: this course is organized externally and additional sign-up steps are required. Sign-up and further course information are available through a Google spreadsheet at https://amos.uni1.de – please declare your interest by filling out the course interest declaration survey as soon as it opens.

    Suggested reading

    http://goo.gl/5Wqnr7

  • 19329912 Project Seminar
    Software Project: Secure Identity (Volker Roth)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: A7/SR 031 (Arnimallee 7)
    

    Comments

    Die Aufgabe wird die Entwicklung einer Software sein. Es wird um sichere Softwareentwicklung gehen. Die Aufgabe wird in Gruppenarbeit gelöst.

  • 19334212 Project Seminar
    Softwareproject: Machine Learning and Explainability for Improved (Cancer) Treatment (Pauline Hiort)
    Schedule: Di 15:00-17:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-02-26)
    Location: T9/K40 Multimediaraum (Takustr. 9)
    

    Comments

    In the software project, we will implement, train, and evaluate various machine learning (ML) methods. The focus of the project is on neural networks (NN) and their explainability. We will compare the methods with different baseline models, such as regression models. The various ML methods will be applied to a specific dataset, e.g., for predicting drug combinations for cancer treatment, and evaluated accordingly. The dataset will be prepared by us and analyzed using the implemented methods. Additionally, we will focus on explainability to ensure that the predictions of the ML models are understandable and interpretable. For this purpose, we will integrate appropriate explainability techniques to better understand and visualize the decision-making processes of the models.

    The programming language is Python, and we plan to use modern Python modules for ML like scikit-learn, and PyTorch. Good Python skills are required. The goal is to create a Python package that provides reusable code for preprocessing, training ML models, and evaluating results with documentation (e.g., using Sphinx) for the specific use case. The software project takes place throughout the semester and can also be conducted in English.

  • 19334412 Project Seminar
    SWP: Szenario-Management in the Future Security Lab (Larissa Groth)
    Schedule: Mi 23.04. 14:00-16:00 (Class starts on: 2025-04-23)
    Location: T9/K63 Hardwarepraktikum (Takustr. 9)
    

    Comments

    The BeLIFE project, part of the working group Telematics & Computer Systems, focuses on improving knowledge transfer and communication in civil security research. A central component of the project is the Future Security Lab, located at the Einstein Center Digital Future (ECDF) in Mitte. The lab welcomes politicians from federal and state levels, as well as representatives from authorities and organizations with security responsibilities.

    Within the software project, students develop concepts to optimize and creatively enhance the existing technical infrastructure of the space. The goal is to increase the usability of the space for scientists and improve the user experience for visitors. To achieve this, the software project consists of several sub-areas, either arising from a specific problem to be solved or requiring creative approaches and ingenuity. Tasks include system administration, interface development, as well as light/sound installation and orchestration. Examples of challenges include the parallel startup of all computers in a network via WakeOn LAN from a web app or optimizing the existing web app for scenario presentation.

    The tasks are exclusively addressed in small groups (3-5 students). Collaboration and code availability are facilitated through the department's own GitLab or a public GitHub. Results should be well-documented, for example, through README files in Git and a well-structured wiki. Modularity and expandability of the developed code, along with thorough documentation, are crucial for the success of this software project!

    Regarding the process, this software project takes place throughout the semester. There are a few mandatory large group meetings with all participants. In addition, there are short weekly meetings where at least one group member reports on the current status. The first date (23.04.25, 14h, K63) will take place at Takustraße 9. At this event, the solutions already implemented will be presented in theory and the problems addressed. A live demo will then take place one week later, on 30.04.2025, in Berlin Mitte at the Future Security Lab, Wilhelmstr. 67, 10117 Berlin. Afterwards, there are a total of three presentation dates: the presentation of an initial approach to problem-solving (14.04.2025), a brief interim presentation (11.06.2025), and the final presentation (16.07.2025).

    Students also regularly have the opportunity to work in the Future Security Lab premises, familiarize themselves with the equipment, and conduct tests.

• Fundamentals of IT Project Management

  0159cA2.6
  • 19335406 Seminar-style instruction
    Project management in agile environments part 2 (Lutz Prechelt)
    Schedule: Mo 08:00-10:00, Fr 16:00-18:00 (Class starts on: 2025-04-14)
    Location: T9/SR 006 Seminarraum (Takustr. 9)
    

    Comments

    Goals

    The students understand several different models of scaled agile software development, that is, agile development encompassing multiple cooperating teams. They understand basic and intermediate methods of hybrid, predictive, and adaptive project management in such agile environments and are able to apply them. They can design a project plan and validate it with suitable methods. They can participate in the project management team of such a hybrid effort and take responsibility for substantial parts of the project management, including managing staff. They can lead a simple project alone.

    Contents

    Students learn the principles, methods and procedures of scaled agile software production using established models (e.g. Scaled Agile Framework) and project management using a recognized methodology (e.g. “Project Management Body of Knowledge” (PMBoK)) and practice their practical application. They develop agile principles and values as well as Scrum and practise both. In addition, they discuss and practise planning the scope of the product and coordinating several teams working together on it, the necessary processes and the roles involved. They also learn about all areas of project management, discuss their application and practise some of their implementation:

    •     Project creation, definition and project scope planning,
    •     project planning,
    •     project process control, status determination and reporting,
    •     Project organization and embedding a project in the executing organization,
    •     Management without formal power,
    •     project communication,
    •     Leading a project team and quality management

• Professional Internship (10 CP)

  0159cA3.1
  • 19315733 Professional Internship
    Internship in Industry (Volker Roth)
    Schedule: -
    Location: keine Angabe
    

    Additional information / Pre-requisites

    at least six weeks (240 hours) outside the university

    Comments

    Contents

    Internships play an important role in the course of study in computer science and offer a perspective on possible future job opportunities for our students. The purpose of the internship is to get to know everyday life on the job and to apply the knowledge and skills acquired during the studies in practice.

    The classes that accompany the internship offer an opportunity for intense preparation and reflection. Students learn about the job market and about the application process and can share their practical experiences.

    Additionally, students learn to appreciate the soft skills necessary on the job, and to evaluate the relationship between a university education and on-the-job requirements.

    Suggested reading

    Exemplarische Praktikumsberichte sind beim Praktikumsbeauftragten einsehbar.

• Teaching Methodology for Computer Science Education: Selected Topics

  0556aA1.1
  • 19323311 Seminar
    Selected Topics of Computer Science Education (Ralf Romeike)
    Schedule: Di 09:00-12:00 (Class starts on: 2025-04-15)
    Location: keine Angabe
    

    Comments

    Various key aspects will be offered, such as:

    • particular problems of computer science teaching and learning according to the type of school (schulartbezogenes Lehren und Lernen von Informatik)
    • particular experimental learning environments und experimental access to selected topics
    • education for sustainable development (Bildung für Nachhaltige Entwicklung (BNE))
    • design and analysis of tasks which are beneficial for learning
    • differentiation and handling of heterogeneity
    • computer science learning in out-of-school learning environments and in pupils' labs
    • multidisciplinary teaching
    • practical teaching experiences in complexity-reduced teaching-learning situations in the teaching-learning lab/pupils' lab
    • gender and diversity in computer science classes

• Teaching Methodology for Computer Science Education: Development, Evaluation, and Research

  0556aA1.2
  • 19323411 Seminar
    Development, Evaluation and Research (Viktoriya Olari)
    Schedule: Do 09:00-12:00 (Class starts on: 2025-04-17)
    Location: KöLu24-26/SR 017 (vorrang Schülerlabor) (Königin-Luise-Str. 24 / 26)
    

    Comments

    Various key aspects will be offered, such as:

    • particular problems of computer science teaching and learning according to the type of school (schulartbezogenes Lehren und Lernen von Informatik)
    • particular experimental learning environments und experimental access to selected topics
    • education for sustainable development (Bildung für Nachhaltige Entwicklung (BNE))
    • design and analysis of tasks which are beneficial for learning
    • differentiation and handling of heterogeneity
    • computer science learning in out-of-school learning environments and in pupils' labs
    • multidisciplinary teaching
    • practical teaching experiences in complexity-reduced teaching-learning situations in the teaching-learning lab/pupils' lab
    • gender and diversity in computer science classes

• Elective module: Computer Science teaching methodology

  0556aA1.72
  • 19309416 Research Seminar
    Research Seminar: Computer Science Education (Ralf Romeike)
    Schedule: Do 14:00-16:00 (Class starts on: 2025-04-17)
    Location: keine Angabe
    

    Additional information / Pre-requisites

    Target audience

    This research seminar is intended for master's students in computer science education (teacher training related).

    Comments

    Presentations of research, bachelor and master theses as well as original papers in Computer Science Education.

    Suggested reading

    Wird während des Semesters geklärt. / To be determined during the semester.

• Student Teaching Lab: Computer Science (Subject 2)

  0557aA1.3
  • 19314911 Seminar
    "Schulpraktische Studien" in Teaching Computer Science: Introductory Seminar (Ralf Romeike)
    Schedule: Mi 10:00-12:00 (Class starts on: 2025-04-16)
    Location: keine Angabe
    

    Comments

    Refer to German description. Courses of Computer Science Education are part of the German teacher-training and held in German only.

• Modules w/o courses in this semester

  37 Modules
  • Impacts of Computer Science 0086cA3.1
  • Fundamentals of Computer Systems 0086cB1.1
  • Research Lab 0086cB1.2
  • Computer Architecture 0087dA1.8
  • Non-sequential and Distributed Programming (Teacher Training Program) 0087dA2.5
  • Impacts of Computer Science 0087dA2.6
  • Social Aspects of Computer Science 0087dA2.7
  • Image Processing 0089cA1.1
  • Medical Image Processing 0089cA1.10
  • Model-driven Software Development 0089cA1.11
  • Pattern Recognition 0089cA1.12
  • Network-Based Information Systems 0089cA1.13
  • Project Management 0089cA1.14
  • Project Management (Specialization) 0089cA1.15
  • Computer Security 0089cA1.16
  • Semantic Business Process Management 0089cA1.17
  • Software Processes 0089cA1.18
  • Compiler Construction 0089cA1.19
  • Computer Graphics 0089cA1.2
  • Distributed Systems 0089cA1.20
  • XML Technology 0089cA1.21
  • Practices in Professional Software Development 0089cA1.22
  • Advanced Topics in Data Management 0089cA1.29
  • Computer Vision 0089cA1.3
  • Database Technology 0089cA1.4
  • Fundamentals of Software Testing 0089cA1.7
  • Artificial Intelligence 0089cA1.9
  • Advanced Algorithms 0089cA2.1
  • Model Checking 0089cA2.2
  • Cryptography and Security in Distributed Systems 0089cA2.8
  • Semantics of Programming Languages 0089cA2.9
  • Operating Systems 0089cA3.1
  • Selected Topics in Technical Computer Science 0089cA3.12
  • Telematics 0089cA3.5
  • Starting a Business in IT 0159cA2.2
  • Social Aspects of Computer Science 0159cA2.3
  • System Administration 0159cA2.7