Seminars

The central registration for all computer science seminars will open on March 3rd.

This system is used to distribute students among the available seminars offered by the CS department. To register for any of the seminars, you have to register here until April 8th, 23:59 CET. You can select which seminar you would like to take, and will then be automatically assigned to one of them on April 11th.

Please note the following:

We aim to provide a fair mapping that respects your wishes, but at the same time also respects the preferences of your fellow students.
Experience has shown that particular seminars are more popular than others, yet these seminars cannot fit all students.
Please only select seminars if you are certain that you actually do want to complete a seminar this semester. If you have already obtained sufficient seminar credits, or plan to take other courses this semester, feel free not to choose any seminars. Students who drop out of seminars take away places from those, who might urgently need a space or are strongly interested in the topic.
We encourage those students who wish to take a seminar this semester, to select their preferences for all available seminars, which eases the process to assign students that do not fit the overly popular seminars to another, less crowded one. So if you are serious about taking a seminar this semester, please select at least three seminars (with priority from "High" to "Low").
If you urgently need to be assigned to a seminar in the upcoming semester, choose at least five seminars (with priority from "High" to "Low"). We will then guarantee that you will be assigned to a seminar (yet not necessarily one of your choice).
If you are really dedicated to one particular seminar, and you do not want any other seminar, please select the "No seminar" as second and third positive option. However, this may ultimately lead to the situation that you are not assigned to any seminar. Also, choosing "No seminar" as second/third option does not increase your chances of getting your first choice.

The assignment will be performed by a constraint solver on April 11th, 2025. You will be added to the respective seminars automatically and be notified about this shortly thereafter. Please note that the assignment cannot be optimal for all students if you drop the assigned seminar, i.e., make only serious choices to avoid penalty to others.

Advanced Time Series Analysis: From Probabilistic to Foundational Models by Isabel Valera

Time series analysis studies data that change as a function of time, such as stock market prices, weather patterns, or household electricity consumption. This seminar covers advanced techniques for analyzing time series, starting with probabilistic methods and progressing to state-of-the-art deep learning approaches, including neural architectures and foundation models. We will also explore connections between time series and other modalities, such as text and images/videos, to offer a comprehensive view of the field. The aim is for students to critically assess existing methods, understand their strengths and limitations, and identify potential directions for future research.

The seminar begins with three introductory lectures to establish foundational concepts, followed by three main blocks on time series analysis: classical approaches, modern deep leanring architectures, and foundational models.

For more info visit: https://cms.sic.saarland/tsa25/

Requirements: Pre-requisites: This seminar aims primarily at master students in Computer Science, DSAI or related fields, who have prior knowledge of machine learning. Participants should have already taken one or several courses related to machine learning, e.g., core machine learning, elements of machine learning, linear algebra, neural networks, etc.

Evaluation based on a presentation, participation in panel discussions and a final report.

Places: 12

Advanced Topics in Program Analysis by Rayna Dimitrova

How can a software developer ensure that the software they have designed does what it is supposed to do? Program analysis is an area of computer science that is concerned with the development of methods and tools that assist programmers in developing correct and robust programs. This includes obtaining a formal understanding of complex programs, automatically verifying that programs work correctly as intended, and automatically repairing, generating, and optimizing code. Program analysis techniques are nowadays part of the software design process at companies such as Amazon, Facebook, Google, and Microsoft. In this seminar, we will read and discuss research papers that present the state of the art in program analysis.

The seminar will be held in English.

Requirements: There are no formal prerequisites for this seminar. However, participants are expected to have a strong interest in formal verification and logical reasoning, and, having taken the Verification lecture would be helpful.

Places: 12

Advanced Topics of Computer Vision and Computer Graphics in the Age of Artificial Intelligence by Christian Theobalt, Rishabh Dabral, Lin Geng Foo, Xilong Zhou

Computer Vision strives to develop algorithms for understanding, interpreting and reconstructing information about real-world scenes from image and video data. Computer Graphics focuses on image synthesis: algorithms to build and edit static and dynamic virtual worlds and to display them in photorealistic or stylized ways. In recent years, these fields have converged more and more. Both Computer Vision and Computer Graphics create and exploit models describing the visual appearance of objects and scenes, while the most successful models heavily utilize ideas from Machine Learning. In this seminar series, we will cover advanced research topics that cross the boundaries between the fields of Computer Vision, Computer Graphics, and Machine Learning. The seminar will discuss state-of-the-art research papers and concepts from various topic domains, such as:

- image and video generation, editing, and analysis,
- multi-view geometry and reconstruction,
- computational photography and videography,
- shape matching,
- neural rendering and scene representation,
- 3D / 4D reconstruction and novel view rendering
- pose estimation, tracking, and character animation,
- deep learning for computer vision and computer graphics,
- visual generative modeling.

Seminar webpage: https://vcai.mpi-inf.mpg.de/teaching/vcai_seminar_2025/index.html

Requirements: This seminar is aimed at graduate students in computer science or related fields. Successful completion of Computer Graphics 1 and Image Processing and Computer Vision is recommended, but not strictly required.

Places: 10

AI Coding Assistants: Hype or Game Changer? by Sven Apel, Kallistos Weis, Marvin Wyrich, Norman Peitek

Who needs human peers for software development when you have an AI that is always available and never disagrees? AI coding assistants are revolutionizing the software world and promise to make our lives significantly better. But is that really the case? How helpful are code explainers? How accurate is automatically generated code? Can poor output be prevented through good prompt engineering?

In this seminar, you will first gain hands-on experience through guided exercises using AI coding assistants such as GitHub Copilot. Then, you will explore a research question related to AI coding assistants by reviewing scientific literature and conducting a small, self-designed study with your fellow seminar participants. Finally, the research question of your study, the results of the initial exploration, and lessons learned will be presented in a short talk and a written seminar paper.

Kick-Off Meeting: Thursday, April 17th
The seminar takes place Thursdays from 12:00 - 14:00 (~11 sessions in sum)

Participation in all sessions is mandatory.

Requirements: This seminar is open to motivated Bachelor and Master students who are eager to try out AI coding assistants in practice while critically and empirically examining their promised benefits. Previous experience with AI coding assistants is not necessary, but basic software engineering and programming knowledge is.

Places: 10

🌍 AI for the Global South – Block Seminar by Vikram Kamath Cannanure, Ingmar Weber

Artificial Intelligence (AI) and Large Language Models (LLMs) are transforming education, healthcare, and agriculture worldwide. However, challenges in the Global South—including digital inequality, language representation, and ethical concerns—demand context-aware AI solutions. This seminar explores how AI, including LLMs, can be leveraged to support learning, healthcare, farming, and social development in resource-constrained environments.

The Global South refers to low- and middle-income countries, primarily in Africa, Latin America, Asia, and the Pacific, that face economic and social development challenges. We will review key papers on AI applications in the Global South, analyze case studies of AI-driven interventions (e.g., chatbots for education, AI in healthcare access, AI-powered farming tools), and discuss the limitations and biases inherent in current AI models. Additionally, we will engage in hands-on exploration of AI-powered tools, critically examining their usability in diverse sociocultural and infrastructural contexts.

The seminar is open to both master’s and bachelor’s students and does not require prior AI knowledge. However, familiarity with fields such as Human-Computer Interaction (HCI), Learning Sciences, AI Ethics, and ICT4D (Information and Communication Technologies for Development) will be beneficial. This seminar welcomes students from all faculties at UdS. Active participation in discussions and activities is expected, as we aim to collaboratively design inclusive, context-aware AI solutions.

Learning Objectives:
By completing this seminar, you will be able to:
• Analyze the potential and limitations of AI-driven systems in the Global South.
• Evaluate ethical concerns, including bias, accessibility, and transparency in AI models.
• Explore LLM-powered applications for education, healthcare, farming, and social impact.
• Generate research and design ideas for AI solutions tailored to low-resource settings.

Grading:
• 20% Daily reading posts (summary and reflections on assigned papers).
• 30% Discussion lead (10-minute paper presentation, once per student).
• 40% Final report (2,000–3,000 words on AI and LLMs in the Global South).
• 10% Contributions to in-class discussions.

🌍 AI for the Global South – Block Seminar

📅 Dates: September 26 – October 10, 2025
📌 Sessions: Monday, Wednesday, and Friday
🕘 Time: 2:00 – 4:00 PM

📖 Day 1 (Friday, September 26, 2025) – Introduction & Digital Inequality
🧠 Day 2 (Monday, September 29, 2025) – LLMs for Learning
🏥 Day 3 (Wednesday, October 1, 2025) – AI in Healthcare
🌱 Day 4 (Friday, October 3, 2025) – AI in Farming
⚖️ Day 5 (Monday, October 6, 2025) – AI Ethics
🎙️ Day 6 (Wednesday, October 8, 2025) – Guest Lecture
🚀 Day 7 (Friday, October 10, 2025) – Participatory AI Design & Future Directions

Requirements: Strong motivation statement to attend. Your motivation statement should discuss your motivation to work in the global south and your interest/skills in AI.

Places: 15

Block Seminar Machine Learning for Natural Language Processing (Fall 2025) by Dietrich Klakow

Deep learning is the predominant machine learning paradigm in natural language processing (NLP). This approach not only gave huge performance improvements across a large variety of natural language processing tasks.

For more information and the specific theme of this semester see:

https://www.lsv.uni-saarland.de/block-seminar-machine-learning-for-natural-language-processing-fall-2025/

Places: 8

Causethical Machine Learning 2.0 by Isabel Valera

Now in its second iteration, this seminar explores the intersection of causality with robustness, interpretability, and fairness in machine learning, exploring how causal reasoning can help build more reliable, explainable, and fair AI systems. Structured into three core themes : Robustness, Interpretability, and Fairness the seminar engages participants in an in-depth exploration of causal theory, methodological innovations, and real-world applications.

Each session will feature discussions on recent research, student-led paper presentations, and critical engagement with open problems in the field. By blending theoretical insights with practical motivation, this seminar provides students with a deep, structured understanding of how causal methods contribute to the development of Responsible and Ethical AI.

For more info visit: https://cms.sic.saarland/causal/

Evaluation based on a presentation, participation in panel discussions and a final report.

Places: 12

Coping with computational hardness: approximation, moderately exponential-time, and parameterized algorithms by Daniel Marx

Most optimization problems and combinatorial search problems are NP-hard, hence we do not expect to be able to find polynomial-time algorithms to solve exactly. But even for such problems, it is still possible to prove rigorous theoretical results that show the existence of algorithms that solve the problem more efficiently than naïve or brute force approaches. Approximation algorithms do not provide an optimal solution, but there is a provable bound on the quality of solution they find. The field of moderately exponential-time algorithms designs algorithms that searches a much smaller (but still exponential) solution space than brute force algorithms do. The running time of a parameterized algorithm is polynomial in the input size, but possibly exponential (or worse!) in some well-defined parameter of the input.

Designing algorithms of this form often requires deep insights into the nature of the problem and clever algorithmic/combinatorial ideas. In this seminar, we will read, present, and discuss research results with the goal of seeing how these algorithmic paradigms can be applied problems in different domains.

Requirements: A solid background in algorithms and some familiarity with concepts in optimization is necessary for this seminar, as well as a general affinity towards mathematical proofs.

Places: 10

Cybersecurity in Organizational Practice by Jonas Hielscher, Maximilian Golla, Ben Stock

In this seminar, we will learn how cybersecurity is practically implemented in organizations (enterprises, public agencies, NGOs, etc.) and discuss why academic cybersecurity concepts are often not followed in practice. We will read and discuss papers on cybersecurity in organizations, frequently utilizing human-centered research methods such as interviews, surveys, focus groups, and case studies.

We will read various recent scientific publications on cybersecurity in organizational practice and foundational papers, some of which have been around for over two decades. We will discuss those papers in the seminar based on presentations by student teams. In team assignments, there will be tasks in which the viewpoint of specific organizational stakeholders (e.g., the CEO) has to be taken, and their position towards a cybersecurity strategy must be defended against other stakeholders. Throughout the seminar, we will reflect upon our own (current and future) experience with cybersecurity in organizational practice. We will learn to negotiate cybersecurity strategies with other stakeholders in our future professions.

More information: https://cms.cispa.saarland/orgsec25/

Requirements: While there are no formal requirements, students should be interested in human-centered security research methods and are expected to familiarize themselves with them.

Places: 12

Data-driven Understanding of the Disinformation Epidemic (DUDE) by Yang Zhang

Arguably, one of the greatest inventions of humanity is the Web. Despite the fact it revolutionized our lives, the Web has also introduced or amplified a set of several social issues like the spread of disinformation and hateful content to a large number of people.

In this seminar, we will look into research that focuses on extracting insights from large corpus of data with the goal to understand emerging socio-technical issues on the Web such as the dissemination of disinformation and hateful content. We will read, present, and discuss papers that follow a data-driven approach to analyze large-scale datasets across several axes to study the multi-faceted aspects of emerging issues like disinformation.

During this seminar, the participants will have the opportunity to learn about state-of-the-art techniques and tools that are used for large-scale processing, including, but not limited to, statistical techniques, machine learning, image analysis, and natural language processing techniques.

Requirements: There are no formal prerequisites for this seminar. Despite this fact, it will be helpful if the participants have a basic understanding of machine learning and data mining.

Places: 20

Defining and Measuring Abstract Concepts in NLP by Vagrant Gautam, Dietrich Klakow

NLP papers commonly use various abstract concepts like “interpretability,” “bias,” “reasoning,” “stereotypes,” and so on. Each subfield has a shared understanding of what these terms mean and how we should treat them, and this shared understanding is the basis on which datasets are built to evaluate these abilities, metrics are proposed to quantify them, and claims are made about systems. But what exactly do these terms mean? And, indeed, what should they mean, and how do we measure that? These questions are the focus of this seminar on defining and measuring abstract concepts in NLP.

In 2-week cycles, we will cover various concepts in NLP, reading papers that analyze or critique how a given concept is used, and then using this as a lens to read, discuss, and critique 2 or more recent NLP papers that use that concept. We will also try to reimagine how we would run these projects and write these papers in light of what we have learned.

For the reading list and more information on course requirements and grading, see https://www.lsv.uni-saarland.de/upcoming-courses/seminar-defining-and-measuring-abstract-concepts-in-nlp-summer-2025/

Places: 7

Equality Saturation by Sebastian Hack

Equality saturation is an emerging technique for program and query optimization developed in the programming language community. It performs term rewriting over an E-graph, a data structure that compactly represents a program space. In this seminar we look at applications of E-graphs and equality saturation for program optimization, equality saturation algorithms, and the theoretical foundations of equality saturation that are rooted in automated reasoning and database theory.

Requirements: Compiler Construction Core Lecture

Places: 8

GameCraft: Spielmechaniken und Spiele-Prototyping by Pascal Lessel, Maximilian Altmeyer (HTW), Antonio Krüger, André Miede (HTW)

Diese Veranstaltung ist eine hochschulübergreifende Veranstaltung zusammen mit der Hochschule für Technik und Wirtschaft des Saarlandes. Die Veranstaltung findet auf Deutsch statt.

Studierende werden ein existierendes (und selbst ausgesuchtes) Open Source Spiel auf spielerische Schwächen und Verbesserungsmöglichkeiten hin analysieren (sowohl eigenständig als auch auf Basis von Playtests), Erkenntnisse dokumentieren, Verbesserung auf Ebene der Spielmechaniken konzipieren sowie in das Spiel prototypisch einbauen und durch erneute Playtests zeigen, dass diese tatsächlich auch effektiv sind. Zum Ende des Semesters (d.h. Ende September), soll ein Videovortrag erstellt werden, der die Ergebnisse obiger Punkte darstellt.

Termin: Mittwochs, 10:30–11:30, ab 16.04.2025 (zusätzlich zu Videomaterial)
(Anwesenheitspflicht)

Abschlussveranstaltung am 24.09.2025 10:30-16:00 (bitte nur eine Priorität vergeben, wenn Sie auch an diesem Termin anwesend sein können).

Ausführliche Informationen zu den Terminen, Inhalten, Aufgaben und der Benotung finden Sie hier: https://umtl.cs.uni-saarland.de/teaching/summer-2025/seminar-gamecraft-spielemechaniken-und-spiele-prototyping.html

Requirements: Sie sollten sich selbst als Konsument von Spielen sehen (egal ob analog oder digital) und ein Gespür für gute Spielemechaniken haben.

Sie sollten solide Programmierkenntnisse vorweisen können, um das von ihnen gewählte Open Source Spiel erweitern zu können.

Sie sollten bereit sein, an allen Veranstaltungsterminen teilzunehmen, unabhängig ob diese an der HTW oder der UdS stattfinden (inkl. der Abschlussveranstaltung in den Semesterferien).

Sie besitzen einen Laptop, den Sie in den Veranstaltungspräsenzterminen mitbringen können und dessen Hardware es erlaubt, dass Playtests mit Ihrem ausgewählten Spiels durchgeführt werden können.

Places: 12

Generative AI for Interactive Systems by Ashwin Ram, Martin Schmitz, Jürgen Steimle

Recent advances in Generative AI are reshaping how we interact with technology, opening the door to innovative interfaces and new modes of human-computer interaction. This seminar will explore how Generative AI-driven techniques reshape future interfaces. Through a combination of paper readings, discussions, and presentations, students will develop a deeper understanding of key Generative AI techniques within the context of HCI while critically evaluating their role in shaping next-generation user experiences.

Seminar page: https://hci.cs.uni-saarland.de/seminar-interacting-with-generative-ai-summer-term-2025/

Requirements: This is an HCI-centric course. Participants must have completed at least one of the following courses (or an equivalent course at another university): the core lecture “Human-Computer Interaction” or the lecture “Interactive Systems”.

Places: 10

Generative Models in Computer Vision (GMCV) by Jan Eric Lenssen, Mohammad Asim

In this seminar we will discuss the diverse set of paradigms for generative modeling in the area of computer vision. We will cover both seminal works, such as diffusion models, flow matching, and sequential generation paradigms, as well as recent advances in generative modeling for solving inverse problems in 2D and 3D computer vision, such as conditional object and scene generation/reconstruction, novel view synthesis, in-painting, and image super-resolution.

The seminar will consist of an introductory meeting with a lecture at the beginning of the semester introducing the field and distributing papers, and a two-day block course in the semester break covering paper presentations and discussions. Students are expected to read into their assigned paper, the related literature, prepare a talk as well as a paper summary with critical discussion.

Website: https://www.mpi-inf.mpg.de/departments/computer-vision-and-machine-learning/teaching/courses-1/ws-2024/2025-jan-seminar

Requirements: The student has a solid understanding of of Machine Learning, Computer Vision and feels comfortable with Neural Networks (for example through lectures High Level Computer Vision, Neural Networks: Theory and Implementation, or Machine Learning).

Places: 10

Hardware Accelerated Graphics with Modern Vulkan by Hugo Devillers, Prof. Philipp Slusallek

We often take GPU acceleration for granted, but how does it work ?
Answering this question takes us from theory to the bleeding-edge of industry standards.

This seminar starts with a top-down introduction to GPU programming and explores them through the eyes of the modern Vulkan API.
Students will learn about the fundamentals of compute and graphics pipelines and put these learnings immediately into a practical project.
After this point, students will be paired up and take their project in one of multiple topics:

* Advanced Compute
* Modern shading languages
* Raytracing pipelines
* Shadow Mapping
* Mesh Shaders
* Voxel raytracing
* Software-defined rasterization
* Open-ended: More topics TBD/available on request

At the end of the seminar students will be expected to give a ~half hour presentation on their topic, including a short live demo.

Requirements: NO prior knowledge of Vulkan itself, OpenGL, DirectX or similar is required: the initial sessions of the seminar will ensure everyone gets up to speed.

We assumes previous familiarity with the concepts discussed in the CG1 lecture, therefore that course is a requirement.
Familiarity with C++, CMake and debuggers will be critical in your success. This isn't a programming lecture!

Places: 12

Imprecise Probabilistic Machine Learning by Krikamol Muandet

This seminar explores the emerging field of imprecise probabilistic machine learning (IPML). While probability theory is the standard mathematical framework for modeling uncertainty and randomness in machine learning, its reliance on single, precise probability distributions often falls short when capturing the multifaceted uncertainties inherent in complex real-world systems. This limitation can lead to undesirable model behavior in practice. To address this, researchers are increasingly turning to generalizations of standard probability theory, encompassing approaches like Dempster-Shafer theory, interval-valued probabilities, the Choquet integral, upper/lower probabilities, and comparative probabilities. Though distinct, these methods all fall under the unifying framework of imprecise probability (IP).

This seminar offers participants a deep dive into the theoretical foundations and practical applications of imprecise probability (IP) in machine learning. Through the reading, presentation, and discussion of curated research papers, we will explore the field's breadth, from philosophical debates surrounding the nature and interpretation of probability to cutting-edge applications in areas such as classification, conformal prediction, out-of-distribution generalization, reinforcement learning, causal inference, foundation models, and large language models (LLMs).

Course website: https://ri-lab.org/courses/ipml-uds-2025

Requirements: background in the foundation of machine learning and its applications

Places: 10

Interpreting and Analyzing Neural Language Models by Xinting Huang, Michael Hahn

Despite their huge success, neural networks are still widely considered “black-boxes”. In this seminar, we will look into interpretability methods that aim to demystify these models. We will focus on post-hoc interpretability for transformer-based language models, and work on relatively young and burgeoning fields such as Mechanistic Interpretability, which focuses on reverse-engineering model components into human-understandable algorithms. We will read recent papers that involve a diverse set of techniques for interpreting the inner-workings of language models

See the course website for more: https://lacoco-lab.github.io/courses/interpreting-2025

If you register for the course, you may be directly admitted or waitlisted. Final decisions will be made by the end of the first week of Summer semester.

Requirements: Required: Background in machine learning.
Recommended: Background in natural language processing.

Places: 12

Living "AI-ducation" Dashboard by Tomohiro Nagashima, Sarah Malone

The rise of artificial intelligence (AI) is transforming everyday lives, including education, and it requires us a deep understanding of and research insights into its applications and implications in the field. This seminar aims to equip students with the knowledge and skills needed to critically analyze AI in education and contribute to this evolving field. The seminar is jointly taught by Prof. Tomohiro Nagashima in the CS department (https://tomonag.org/) and Dr. Sarah Malone in the Education Science department (https://www.uni-saarland.de/lehrstuhl/bruenken/personen/dr-sarah-malone.html), and it targets students in both departments.

During the seminar, students will collaboratively design and develop a "Living AI-education Dashboard," a dynamic resource that summarizes and visualizes current research, trends, and data on AI in education. Through project-based learning, students will gain hands-on experience in data visualization, dashboard creation, dashboard design, and research methods (e.g., how to conduct systematic literature review and user-centered research). Students would also interact with education stakeholders to gain deep insights into what different stakeholders would wish to see on the dashboard, and incorporate their insights into the design. They will also develop interdisciplinary thinking by integrating concepts from both computer science and education science and through collaborations across the domains. The course is taught by an interdisciplinary team that encourages collaboration between departments and prepares students to tackle complex, real-world problems.

The seminar will be offered on Mondays 10-12:00 (location TBD).

Feel free to contact mailto:nagashima@cs.uni-saarland.de for any questions. Find out more about the seminar here: https://tomonag.org/aiducation/

*Note that you may not take the seminar this semester if you took the first iteration in WS2024-25.

Requirements: It is highly recommended that students are familiar with data visualization and its tools (e.g., Tableau). However, it is not a strict requirement; please describe your experience with data vis in your application.

Places: 10

Mechanism Design Without Money by Kurt Mehlhorn, Javier Cembrano, Golnoosh Shahkarami

Mechanism design is an area of algorithmic game theory that focuses on coordinating players' interests to achieve collective decisions. While a common approach involves financial incentives, monetary transactions are unethical or impractical in many real-world scenarios; canonical examples include assigning students to schools, matching organ donors to recipients, placing public facilities, and electing representatives. The field of mechanism design without money explores ways to align individual incentives with socially desirable outcomes in such settings.

Some initial lectures will be taken by the instructors to explain the basics that will help students to select their paper/topic. The seminar is open to all interested students and postdocs. Students aiming to get credit points must give a regular talk and write a short summary of the paper. The presentation needs to be discussed with us at least one week before your scheduled talk.

For further information, visit the seminar website: https://www.mpi-inf.mpg.de/departments/algorithms-complexity/teaching/summer-2025/mechanism-design-without-money

Requirements: This is a theoretical seminar that will require mathematical maturity (in particular, the ability to understand and write formal mathematical proofs) and a good background in algorithms. A proper preparation of your talk will require non-trivial effort. The target audience of this seminar is master students, PhD students, as well as postdocs.

Places: 10

Neural Networks in Brains and Computers by Michael Hahn

We will look into the intersection of machine learning and neuroscience. The main target audience is students with a background in machine learning who are interested in learning about the brain and how it processes information, how artificial neural networks relate to real neurons, how machine learning can help understand the brain better, and how machine learning models may end up aligning with representations found in the brain. The focus will mostly be on vision and language. Thus, this seminar may be particularly interesting if you have a background either in NLP/Computational Linguistics or in Computer Vision. Background in one of the two is certainly enough.

More information: https://lacoco-lab.github.io/courses/brain-2025/

Places: 12

Politics of Security and Privacy by Katharina Krombholz

In this seminar, we will discuss political aspects of security and privacy technology and research. We will discuss both historical and ongoing areas of tension. Some topics are censorship, surveillance, information leakage and other security and privacy challenges that harm individuals, at-risk users and nations.

The dates and all other information can be found in CMS: https://cms.cispa.saarland/psp/

Requirements: You have completed at least on course on cyber security.

Places: 14

Privacy Engineering und Recht by Prof. Dr. Christoph Sorge

Das Seminar „Privacy Engineering und Recht” ist ein interdisziplinäres Seminar für Informatiker und Juristen.
Privacy Engineering verbindet verschiedene Disziplinen wie Informatik und Recht. Diese interdisziplinäre Herangehensweise ermöglicht es, umfassende und innovative Lösungen für Datenschutzprobleme zu entwickeln. Privacy Engineering erfordert die Entwicklung und Implementierung komplexer technischer Lösungen wie Anonymisierung, Pseudonymisierung und Privacy-by-Design. Diese technischen Herausforderungen machen das Feld besonders spannend für diejenigen, die gerne innovative und kreative Lösungen entwickeln.
Das Seminar will die Möglichkeit bieten in den interdisziplinären Austausch zu treten und sich mit den technischen und rechtlichen Herausforderungen des Datenschutzes auseinander zu setzen.

Ablauf:

Vorbesprechung: Einführung und Themenvergabe.
Abstracts und Preprints: Einreichung und Feedback-Runden.
Peer Reviews: Bewertung der Arbeiten durch andere Teilnehmer.
Vorträge: Präsentation der Seminararbeiten.
Abschlussarbeit: Finale Abgabe der ausgearbeiteten Themen

Requirements: Es wird erwartet, dass die Teilnehmer in der Lage sind, Vorträgen in deutscher Sprache zu folgen und Ausarbeitungen in deutscher Sprache im Rahmen des Peer Reviews zu lesen (eigene Vorträge und Ausarbeitungen können aber in deutscher oder englischer Sprache angefertigt werden).

Places: 8

Privacy in Computations and Communications by Lucjan Hanzlik and Sajin Sasy

We use the Internet for all forms of communications and data-driven applications today. Existing systems and solutions that are widely used, often fail to protect its users' privacy. In this seminar, we will first examine different techniques and building blocks that can facilitate digital privacy. We will then explore recent designs for privacy-preserving systems for communications and data processing.

Over the course of the seminar, students will read, review, and present exciting research papers that span privacy enhancing technologies (PETS) and applied cryptography. The seminar will begin with two instructor lead sessions that will provide a high-level overview of the topics and relevant background. Following weeks will be student presentations and discussions. As part of the seminar, each student will present two research papers in a 25 minute, conference-style talk, and lead a 30 minute discussion on their paper.

More information: https://cms.cispa.saarland/pcc/

Requirements: A foundational understanding of security and cryptography is essential to be able to follow and understand the topics of this seminar. Ideally, you have already completed one of the CySec1/CySec2/Security course offerings, as well as the Cryptography course.

Places: 12

Provable Security of Key Exchange Protocols by Doreen Riepel, Cas Cremers

Cryptographic protocols such as TLS and Signal form the foundation of secure communication, ensuring confidentiality, integrity, and authentication for billions of users worldwide. In this seminar, we will look into the theoretical foundations of the underlying protocols. We will examine recent research papers on key exchange and secure messaging that address advanced cryptographic properties (e.g., deniability), specific functionalities (e.g., password-based or hybrid key exchange), and tight security proofs.

Each student will be assigned a research paper to present as a 60 minutes lecture with subsequent discussion. Additionally, the talk should be summarized in a two-page handout. Since these papers are often extensive and contain detailed security proofs, students may concentrate on a specific contribution in coordination with the lecturer. To support this process, the seminar will include two introductory sessions with guidance, practical tips, and an example presentation.

More information: https://cms.cispa.saarland/keyexchange_25/

Requirements: The seminar is designed for Master students with a foundational understanding of cryptography. Prior knowledge of concepts such as security reductions, game-based proofs, and protocol design are beneficial.

Places: 10

Reliability in Modern Cloud Systems by Vaastav Anand, Antoine Kaufmann

Cloud systems power a large fraction of the computing world today. Ensuring that these systems are correct and performant remains a key challenge that continues to bedevil developers. In this seminar, we will explore various themes around the various forms of reliability in modern cloud systems as well as learn about state-of-the-art strategies for mitigating incidents and understanding issues in modern cloud systems today.

Course Website: https://cms.sic.saarland/cldrel_25/

Requirements: Pre-requisites: Programming 2, Software Engineering Lab (Praktikum)
Recommended: Distributed Systems

Places: 20

Reproducible methods in metagenomics by Johanna Schmitz, Jens Zentgraf and Sven Rahmann

In this seminar, we discuss recently published papers that introduced novel methods for metagenomic data analysis, mainly focusing on efficient algorithms and data structures for sequence data.
Starting with the original paper, participants shall explain the underlying method with all necessary background and apply the tool to check the reproducibility of the results in the paper.
To pass the seminar both a presentation (40 min for seminars and 30 min for pro-seminars) and a written report are required.

A kick-off meeting to discuss the organization and possible papers will be held early in the semester. Participation in this kick-off meeting is only possible if you have been assigned to this seminar by the seminar system. You will then receive an email with the exact date and time. To participate in the seminar, participation in the kick-off meeting is mandatory.

Possible topics include:

- data processing (quality control, contamination removal etc.)
- taxonomic classification
- (meta)genome assembly
- metagenomic phylogeny

Requirements: Basic knowledge about algorithms and data structures, e.g., Introduction to Algorithms and Data Structures, Bioinformatik I, or Algorithms for Sequence Analysis

Places: 15

Research Methods in Human-centric Security by Katharina Krombholz

In this seminar, you will learn about empirical methods that are used to research human factors in security and privacy.

More information, including the schedule can be found on https://cms.cispa.saarland/hcs/

Requirements: Ideally, you have completed either a lecture on Security or HCI.

Places: 14

Research Project in "Technology and Self-Care" by Anna Maria Feit, Laura Pissani, Nadine Wagener

This seminar is open only to students who have participated in the "Technology and Self-Care" seminar or who have otherwise gained substantial theoretical experience in this area. To take part, you should be familiar with key concepts such as digital well-being, self-reflection and self-tracking, emotion recognition, mindfulness, and the broader impact of technologies such as social media or chatbots on mental and physical health. You should also have an understanding of ethical considerations in self-care technologies.

In this seminar, students will develop independent research projects that apply their theoretical knowledge to practical research problems. Projects may involve designing and implementing new self-care technologies, such as mobile apps, AI-based support systems, or wearable interfaces. Others may focus on evaluating existing tools through user studies, experiments, or data analysis. Interdisciplinary perspectives from computer science, HCI, psychology, linguistics, and philosophy are encouraged.

Students will work on their projects individually but are encouraged to support each other by forming peer groups of students using similar methods, providing feedback, and participating in each other’s studies. Each student will receive close supervision from a researcher, with regular check-ins for guidance on methodology, execution, and writing. In addition to submitting a project report, there will be a research showcase at the end of the seminar, where students present their work to peers and interested researchers on campus, gaining feedback and experience in research communication.

Note: The seminar takes place on Mondays from 2-4PM. Participation at the kick-off meeting on April 14th is mandatory, make sure to check your Emails for information beforehand. The seminar is designed so that the workload will be higher in the beginning and middle part of the semester.

Requirements: Important: This seminar assumes that you already have a research question and method in mind and have conducted a literature review to support your approach. If you have not taken part in the "Technology and Self-Care" seminar but are strongly interested in participating, or if you wish to work on a topic different from what you proposed in the previous seminar, please contact the lecturer, Anna Maria Feit, via email *before* applying here. Include a short document describing your envisioned project, covering: motivation and context, research question, planned method, expected contributions, and an overview of related literature.

Spots in this seminar are limited to ensure high-quality supervision. Priority will be given to students with a well-developed research plan and prior theoretical experience in this field.

Places: 10

Selected Topics in Mobile Security by Sven Bugiel

In this seminar, we will discuss current results and new problems in the mobile security domain based on relevant scientific papers. Given Android's high popularity among researchers, the selected papers focus on Android. The topics include usability aspects of Android's permission system and security-relevant APIs, security extensions at different Android software stack levels, app analysis, and newly identified attack vectors.

Requirements: The participant should have passed the Adv. Lecture Mobile Security. Additionally, the participant is familiar with basic security and privacy concepts (e.g., attended the Core Lecture Security or Foundations of Cybersecurity)

Places: 9

Spatiotemporal Models and Inference (Block Seminar Fall 2025) by Jonas Wahl, Verena Wolf

In many scientific fields, data is not just tied to a single location or a single moment in time—it evolves over both space and time. Whether tracking the spread of infectious diseases, predicting climate patterns, modeling traffic flows, or analyzing environmental pollution, understanding how variables change across both dimensions is crucial. This is where spatiotemporal modeling comes in.

Spatiotemporal models aim to capture dependencies and relationships in data that vary over time and across geographical locations. Unlike purely spatial or purely temporal models, these approaches integrate both dimensions, allowing us to uncover trends, make predictions, and quantify uncertainties in dynamic systems.
Throughout this seminar, we will explore the foundations of spatiotemporal modeling, discuss cutting-edge methodologies, and learn about real-world applications. To a varying extent, we will cover theoretical underpinnings of spatiotemporal statistics, Bayesian approaches and hierarchical models, and machine learning techniques for handling complex spatiotemporal data. We will also work our way through some coding tutorials.

You can find more detailed information here: https://cms.sic.saarland/spamo/

We're looking forward to meeting you in the seminar!

Requirements: You have successfully participated in a machine/deep learning course, or you have a background in statistical modeling, for instance thanks to a course on statistics or stochastic processes.

Places: 10

Sweat and Survive - The VR Edition by Dr. André Zenner, Felix Kosmalla, Prof. Dr. Antonio Krüger

In this practical seminar, small groups of students (3) will develop a Virtual Reality (VR) fitness application with a twist. Users will be immersed in a virtual environment that guides them through a fitness exercise while motivating them through (virtually) dangerous situations. Each group will be assigned a different exercise to which the virtual environment and feedback should be adapted. In each scenario, the threat level should be adaptable from no danger over medium danger to high danger. Finally, each prototype will be evaluated in a small user study.

More info here: https://umtl.cs.uni-saarland.de/teaching/summer-2025/seminar-the-danger-workout.html

Requirements: - strong programming background
- experience with Unity, C#, and/or VR technology is a plus (but not strictly required)

Places: 12

The Web Security Seminar by Aurore Fass, Giancarlo Pellegrino, Cristian-Alexandru Staicu, Ben Stock

The Web Security Seminar will teach students to present, analyze, discuss, and summarize papers in different areas of Web security. The seminar combines a reading group with (almost) weekly meetings and a regular seminar, where students will write a seminar paper.

Each student will get a topic assigned, consisting of a lead and a follow-up paper. The student will present the follow-up paper in a 20-minute presentation followed by a 10-minute Q&A. Afterwards we will all discuss the lead paper as a reading group. All students must read the lead paper and, before each session, must submit a summary with strengths and weaknesses.

Finally, each student will write a seminar paper on the topic assigned to them, for which the two papers serve as the starting point.

Any use of LLMs/GenAI is strictly forbidden for producing or polishing the text of the seminar papers. We will thoroughly investigate any suspicious text we find in the submitted manuscripts, e.g., via an oral exam in which the student is invited to explain the text. Moreover, the students must write all their text via Overleaf in a project monitored by the organizers of the seminar.

The student will take place Tuesday at 12:15-14:00 and the kickoff will be on 15.04.2025.

More information can be found here: https://cms.cispa.saarland/websecsem_sose25/

Requirements: We expect all students of this seminar to already be familiar with most important web security topics, e.g., XSS, CSP. Moreover, we require students to write a short motivation statement to show their interest in talking this seminar.

Places: 10

Verification of Distributed Systems by Swen Jacobs

Most of our information-processing systems nowadays are distributed - be it large-scale data centers that replicate data in different physical locations, sensor networks that collect data from different places, or simply multi-threaded programs that run on different cores of your CPU. Due to their composition from multiple interacting components, ensuring correctness of these systems is a major challenge. In many application areas, faulty behavior or even short outages of these systems can have severe consequences. Therefore, both industrial and academic research has in recent years developed a range of new methods to formally guarantee certain properties of a given distributed system.

In this seminar, students will learn to present, discuss, and summarize research papers that aim at formalizing and verifying distributed systems, with a focus on timing properties. The seminar is split into two parts. The first part will take the form of reading sessions, where we lay the foundations of the topic. For the second part, each student is assigned a recent paper from the research area. Students will present their paper and will write a seminar paper on the topic assigned to them, taking into account connections to the topics discussed in the seminar.

Requirements: Interest in formal methods and theoretical computer science, as well as basic knowledge about concurrent or distributed systems. Some knowledge of formal methods (e.g. Verification or Automated Reasoning) is recommended.

Places: 12

Wireless Security by Mridula Singh

We use wireless systems to share confidential information, access bank accounts, report heart rate, etc., incentivizing attackers to eavesdrop and manipulate wireless communication. In this seminar, we will discuss the security, privacy, and availability aspects of the widely used wireless systems.

During the first half of the semester, each student will read 5-6 research papers. In the second half, students will work on projects in a team of 2 students. We will meet weekly to discuss the papers and progress of projects. Finally, students will give a 25-minute presentation at the end of the semester.

Requirements: Knowledge of signal processing would be beneficial but optional as long as you are motivated and able to learn relevant fundamentals.

Places: 12