Computer Science

• Project Seminar: Data Management Systems

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  • 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.

• Robotics

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  • 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)
    

• Seminar: Contributions to Software Engineering

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  • 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

• Seminar: Data Management

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  • 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.

• Software Project: Data Management

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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.

• Software Project: Web Technologies

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  • 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

• Seminar: Database Systems

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  • 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.

• Software Technology Project

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  • 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

• Software Project: Artificial Intelligence

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  • 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

• Empirical Evaluation in Computer Science

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  • 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)
    

• Current research topics in Applied Computer Science

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  • 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

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  • 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)
    

• Current Research Topics in Algorithmics

  0089bA2.1
  • 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.

  • 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.

  • 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)
    
  • 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)
    

• Module (lecture+exercise 2+2 hrs/wk) 5

  0089bA2.16
  • 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.

  • 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.

  • 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)
    
  • 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)
    

• 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)
    

• Module (seminar 2 hrs/wk) 5

  0089bA3.14
  • 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.

• Seminar: Computer Systems

  0089bA3.6
  • 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.

• 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

• Numerical Mathematics I

  0084cA1.9
  • 19212001 Lecture
    Numerics I (Claudia Schillings)
    Schedule: Mo 10:00-12:00, Mi 10:00-12:00, zusätzliche Termine siehe LV-Details (Class starts on: 2025-04-14)
    Location: KöLu24-26/SR 006 Neuro/Mathe (Königin-Luise-Str. 24 / 26)
    

    Comments

    Numerical methods for: iterative solution of nonlinear systems of equations (fixpoint and Newton methods), curve fitting, interpolation, numerical quadrature, and numerics of ODE systems.

    Suggested reading

    Stoer, Josef und Roland Bulirsch: Numerische Mathematik - eine Einführung, Band 1. Springer, Berlin, 2005.

    Aus dem FU-Netz auch online verfügbar.

    Link

  • 19212002 Practice seminar
    Practice seminar for Numerics I (N.N.)
    Schedule: Di 08:00-10:00, Di 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/049 Seminarraum (Takustr. 9)
    

• Discrete Mathematics I

  0084cB3.2
  • 19214701 Lecture
    Discrete Mathematics I (Ralf Borndörfer)
    Schedule: Di 14:00-16:00, Do 12:00-14:00 (Class starts on: 2025-04-15)
    Location: T9/SR 005 Übungsraum (Takustr. 9)
    

    Additional information / Pre-requisites

    Target group:

    BMS students, Master and Bachelor students

    Whiteboard:

    You need access to the whiteboard in order to receive information and participate in the exercises.

    Large tutorial:

    Participation is recommended, but non-mandatory.

    Exams:

    1st exam: Thurday July 17, 14:00-16:00, room tba, i.e., in the last lecture
    2nd exam: Thursday October 09, 10:00-12:00, room tba, i.e., in the last week before the lectures of the winter semester start

    Comments

    Content:

    Selection from the following topics:

    • Enumeration (twelvefold way, inclusion-exclusion, double counting, recursions, generating functions, inversion, Ramsey's Theorem, asymptotic counting)
    • Discrete Structures (graphs, set systems, designs, posets, matroids)
    • Graph Theory (trees, matchings, connectivity, planarity, colorings)

    Suggested reading

    • J. Matousek, J. Nesetril (2002/2007): An Invitation to Discrete Mathematics, Oxford University Press, Oxford/Diskrete Mathematik, Springer Verlag, Berlin, Heidelberg.
    • L. Lovasz, J. Pelikan, K. Vesztergombi (2003): Discrete Mathemtics - Elementary and Beyond/Diskrete Mathematik, Springer Verlag, New York.
    • N. Biggs (2004): Discrete Mathematics. Oxford University Press, Oxford.
    • M. Aigner (2004/2007): Diskrete Mathematik, Vieweg Verlag, Wiesbaden/Discrete Mathemattics, American Mathematical Society, USA.
    • D. West (2011): Introduction to Graph Theory. Pearson Education, New York.

  • 19214702 Practice seminar
    Practice seminar for Discrete Mathematics I (Silas Rathke)
    Schedule: Di 16:00-18:00, Do 14:00-16:00 (Class starts on: 2025-04-22)
    Location: A3/SR 119 (Arnimallee 3-5)
    

    Comments

    Content:

    Selection from the following topics:

    • Counting (basics, double counting, Pigeonhole Principle, recursions, generating functions, Inclusion-Exclusion, inversion, Polya theory)
    • Discrete Structures (graphs, set systems, designs, posets, matroids)
    • Graph Theory (trees, matchings, connectivity, planarity, colorings)
    • Algorithms (asymptotic running time, BFS, DFS, Dijkstra, Greedy, Kruskal, Hungarian, Ford-Fulkerson)

• Modules w/o courses in this semester

  173 Modules
  • Operating Systems 0089bA1.1
  • Mobile Communications 0089bA1.10
  • Pattern Recognition 0089bA1.11
  • Network-Based Information Systems 0089bA1.12
  • Semantic Business Process Management 0089bA1.15
  • Semantics of Programming Languages 0089bA1.16
  • Seminar: Artificial Intelligence 0089bA1.19
  • Image Processing 0089bA1.2
  • Seminar: Programming Languages 0089bA1.20
  • Software Project: Mobile Communications 0089bA1.22
  • Software Project: Compiler Construction 0089bA1.23
  • Software Processes 0089bA1.25
  • Advanced Topics in Data Management 0089bA1.26
  • Telematics 0089bA1.27
  • Transactional Systems 0089bA1.28
  • Compiler Construction 0089bA1.29
  • Computer Graphics 0089bA1.3
  • Distributed Systems 0089bA1.30
  • XML Technology 0089bA1.31
  • Telematics Project 0089bA1.32
  • Seminar: Modern Web Technology 0089bA1.34
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA1.37
  • Module (course 2 hrs/wk) 2 0089bA1.38
  • Module (project 1 hr/wk) 3 0089bA1.39
  • Computer Vision 0089bA1.4
  • Module (lecture+exercise 2+1 hrs/wk) 4 0089bA1.40
  • Module (seminar 2 hrs/wk) 5 0089bA1.41
  • Module (lecture+exercise 2+2 hrs/wk) 6 0089bA1.42
  • Module (seminar+practical 1+1 hrs/wk) 7 0089bA1.43
  • Module (project seminar 3 hrs/wk) 8 0089bA1.44
  • Module (lecture+exercise 4+2 hrs/wk) 9 0089bA1.45
  • Module (lecture+exercise 2+2 hrs/wk) 10 0089bA1.46
  • Module (practical 4 hrs/wk) 11 0089bA1.47
  • Module (project 4 hrs/wk) 12 0089bA1.48
  • Seminar: IT Security 0089bA1.49
  • Database Technology 0089bA1.5
  • Module (lecture+exercise 2+2 hrs/wk) 13 0089bA1.50
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA1.51
  • Module (lecture+exercise 2+2 hrs/wk) 15 0089bA1.52
  • Module (project 4 hrs/wk) 16 0089bA1.53
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 17 0089bA1.54
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 18 0089bA1.55
  • Module (project 4 hrs/wk) No. 19 0089bA1.56
  • Module (project 4 hrs/wk) No. 20 0089bA1.57
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 21 0089bA1.58
  • Module (practical 2 hrs/wk (contact hours), 4 CP) No. 22 0089bA1.59
  • Module (practical 2 hrs/wk, 4 CP) No. 23 0089bA1.60
  • Advanced Aspects of Functional Programming 0089bA1.7
  • Computer Security 0089bA1.8
  • Artificial Intelligence 0089bA1.9
  • Model-driven Software Development 0089cA1.11
  • Computer Security 0089cA1.16
  • Compiler Construction 0089cA1.19
  • Computer Graphics 0089cA1.2
  • Practices in Professional Software Development 0089cA1.22
  • Fundamentals of Software Testing 0089cA1.7
  • Software Project: Application of Algorithms 0089bA2.11
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA2.12
  • Module (course 2 hrs/wk) 2 0089bA2.13
  • Module (lecture+exercise 2+1 hrs/wk) 3 0089bA2.14
  • Module (Seminar 2 hrs/wk) 4 0089bA2.15
  • Module (lecture+exercise 4+2 hrs/wk) 6 0089bA2.17
  • Module (lecture+exercise 2+2 hrs/wk) 7 0089bA2.18
  • Module (practical 4 hrs/wk) 8 0089bA2.19
  • Computational Geometry 0089bA2.2
  • Module (project 4 hrs/wk) 9 0089bA2.20
  • Module (seminar 2 hrs/wk) No. 10 0089bA2.21
  • Module (2 lecture + 2 exercise hrs/wk, 5 CP) No. 11 0089bA2.22
  • Module (4 lecture + 2 exercise hrs/wk, 8 CP) No. 12 0089bA2.23
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 13 0089bA2.24
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 14 0089bA2.25
  • Selected Topics in Algorithims 0089bA2.3
  • Advanced Algorithms 0089bA2.4
  • Cryptography and Security in Distributed Systems 0089bA2.6
  • Model Checking 0089bA2.7
  • Seminar: Algorithms 0089bA2.8
  • Advanced Algorithms 0089cA2.1
  • Model Checking 0089cA2.2
  • Cryptography and Security in Distributed Systems 0089cA2.8
  • Module (lecture/integrated exercise 2 hrs/wk) 1 0089bA3.10
  • Module (course 2 hrs/wk) 2 0089bA3.11
  • Module (project 1 hr/wk) 3 0089bA3.12
  • Module (lecture+exercise 2+1 hrs/wk) 4 0089bA3.13
  • Module (lecture+exercise 2+2 hrs/wk) 6 0089bA3.15
  • Module (seminar+practical 1+1 hrs/wk 7 0089bA3.16
  • Module (project seminar 3 hrs/wk) 8 0089bA3.17
  • Module (lecture+exercise 4+2 hrs/wk) 9 0089bA3.18
  • Module (lecture+exercise 2+2 hrs/wk) 10 0089bA3.19
  • Microprocessor Lab 0089bA3.2
  • Module (practical 4 hrs/wk) 11 0089bA3.20
  • Module (project 4 hrs/wk) 12 0089bA3.21
  • Module (lecture+exercise 2+2 hrs/wk) 13 0089bA3.22
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA3.23
  • Module (project 4 hrs/wk) 15 0089bA3.24
  • Module (seminar 2 hrs/wk) No. 16 0089bA3.25
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 17 0089bA3.26
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 18 0089bA3.27
  • Module (2 lecture + 4 exercise hrs/wk, 10 CP) No. 19 0089bA3.28
  • Operating Systems 0089cA3.1
  • Selected Topics in Technical Computer Science 0089cA3.12
  • Telematics 0089cA3.5
  • Project Management 0089bA4.25
  • Module (project 1 hr/wk) 1 0089bA4.26
  • Starting a Business in IT 0089bA4.27
  • Module (lecture/integrated exercise 2 hrs/wk) 2 0089bA4.28
  • Module (course 2 hrs/wk) 3 0089bA4.29
  • Module (project 1 hr/wk) 4 0089bA4.30
  • Module (lecture+exercise 2+1 hrs/wk) 5 0089bA4.31
  • Module (seminar 2 hrs/wk) 6 0089bA4.32
  • Module (lecture+exercise 2+2 hrs/wk) 7 0089bA4.33
  • Module (seminar+practical 1+1 hrs/wk) 8 0089bA4.34
  • Module (project seminar 3 hrs/wk) 9 0089bA4.35
  • Module (lecture+exercise 4+2 hrs/wk) 10 0089bA4.36
  • Module (lecture+exercise 2+2 hrs/wk) 11 0089bA4.37
  • Module (practical 4 hrs/wk) 12 0089bA4.38
  • Module (project 4 hrs/wk) 13 0089bA4.39
  • Module (lecture+exercise 2+2 hrs/wk) 14 0089bA4.42
  • Module (lecture+exercise 2+2 hrs/wk) 15 0089bA4.43
  • Module (lecture+exercise 2+2 hrs/wk) 16 0089bA4.44
  • Module (project 4 hrs/wk) 17 0089bA4.45
  • Module (seminar 2 hrs/wk) No. 18 0089bA4.46
  • Module (seminar 2 hrs/wk) No. 19 0089bA4.47
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 20 0089bA4.48
  • Module (2 lecture + 4 exercise hrs/wk, 8 CP) No. 21 0089bA4.49
  • Digital Video 0089bA4.5
  • Module (2 lecture + 2 practical hrs/wk, 5 CP) No. 22 0089bA4.50
  • Module (2 lecture + 2 practical hrs/wk, 5 CP) No. 23 0089bA4.51
  • Module (practical 2 hrs/wk, 4 CP) No. 24 0089bA4.52
  • Module (practical 2 hrs/wk, 4 CP) No. 25 0089bA4.53
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 26 0089bA4.54
  • Module (4 lecture + 2 exercise hrs/wk, 10 CP) No. 27 0089bA4.55
  • E-Learning Platforms 0089bA4.6
  • Module (project 1 hr/wk) 1 0089bA4.7
  • Medical Image Processing 0089bA4.9
  • Special Lecture: Graph Theory 0084bC3.3
  • Special Lecture: Cryptography 0084bC3.6
  • Main Lecture: Logic and Model Theory 0084bC4.1
  • Probability and Statistics I 0084cA1.8
  • Algebra and Number Theory 0084cB2.5
  • Numerical Mathematics II 0084cB3.4
  • Advanced Module: Combinatorics and Graph Theory 0280aA2.1
  • Specialization Module: Discrete Geometry and Optimization 0280aA2.2
  • Special Module: Visualization 0280aA4.6
  • Algorithmische Bioinformatik 0260aA1.4
  • Statistics I for Students of Life Sciences 0260aA2.5
  • Statistics II for Students of Life Sciences 0260aA2.6
  • Diskrete Mathematik 0262aA1.1
  • Algorithmen in der Systembiologie 0262aA1.3
  • Fortgeschrittene Algorithmen in der Bioinformatik 0262aA1.4
  • Sequenzanalyse und molekulare Evolution (A) 0262aA2.1
  • Vertiefung statistischer Methoden in Genetik und Bioinformatik (B) 0262aA2.10
  • Sequenzanalyse und molekulare Evolution (B) 0262aA2.2
  • Mathematische Aspekte und Algorithmen der Strukturbiologie (A) 0262aA2.3
  • Mathematische Aspekte und Algorithmen der Strukturbiologie (B) 0262aA2.4
  • Simulating Molecular and Cellular Processes (A) 0262aA2.5
  • Simulating Molecular and Cellular Processes (B) 0262aA2.6
  • Advanced Statistical Methods in Genetics and Bioinformatics (A) 0262aA2.9
  • Theoretical Physics 1 0182aA2.1
  • Theoretical Physics 2 0182aA2.2
  • Atomic and Molecular Physics 0182aA4.2
  • Solid State Physics 0182aA4.3
  • Biophysics 0182aA4.4
  • Introduction to Astronomy and Astrophysics 0182aA4.5
  • Advanced Module: Epistemology and Philosophy of Science 0044cB1.1
  • Advanced Module: Philosophy of Language and Hermeneutics 0044cB1.2
  • Advanced Module: Metaphysics and Ontology 0044cB1.3
  • Advanced Module: Ethics 0044cB1.4
  • Advanced Module: Political/Social Philosophy and Anthropology 0044cB1.5
  • Advanced Module: Aesthetics 0044cB1.6
  • Cognitive and Experimental Psychology 0281bA1.1
  • Differential and Personality Psychology 0281bA1.3
  • Social Psychology 0281bA1.4
  • Developmental Psychology 0281bA1.5