Veranstaltungsverzeichnis

Department of Computing Science

• English course offer for exchange students :
• School of Computing Science, Business Administration, Economics and Law
• Department of Computing Science

Summer semester 2026 46 Seminars

VAK Course Number	Title	Type Lecture Preliminary studies Advanced courses Practical course Colloquium Research group Workgroup Project group Council conference Internship Language course Subject didactics Excursion Tutorial Committee	SWS Semester weekly hours	Teachers	Degree
2.01.803	Verification of Probabilistic Programs Tuesday, 14:00 - 16:00, Weekly (from 07.04.26) Friday, 14:00 - 16:00, Weekly (from 10.04.26) Description: Probabilistic programs are ordinary programs with the ability to sample from probability distributions. This ability often admits simpler or more efficient (at least on average) solutions than deterministic programs. At the same time, writing correct probabilistic programs is challenging, because they cannot be tested reliably. In this course, we will thus study techniques to formally reason about the correctness of probabilistic programs.	Lecture	4	Prof. Dr. Christoph Matheja M. Sc. Roberto Pettinau	Master of Education Bachelor Erweiterungsfach Master
2.01.-CAUSE	Seminar of the RTN CAUSE The course times are not decided yet. Description: The seminar is dedicated to the ongoing scientific exchange and cooperation of the memvers of the RTN CAUSE at Oldenburg.	miscellaneous	-	Prof. Dr. Sebastian Lehnhoff Prof. Dr. Verena Klös Prof. Dr. Heike Wehrheim Prof. Dr. Martin Georg Fränzle
2.01.5120	Digitalised Energy Systems Co-Simulation Friday, 10:00 - 12:00, Weekly (from 10.04.26) Monday, 12:00 - 14:00, Weekly (from 13.04.26) Description:	Lecture	4	Jörg Bremer	Master
2.01.369-C	Selected Topics in Nanorobotics and Nanomanufacturing in Scanning Electron Microscopes (SEM): Towards Intelligent Nanofactories The course times are not decided yet. Description: Description: This seminar introduces graduate students to the emerging field of SEM-enabled nanomanufacturing and nanorobotics, where scanning electron microscopes evolve from high-resolution imaging systems into intelligent, multifunctional nanofactories. By integrating tools such as Focused Ion Beam (FIB), Gas Injection Systems (GIS), and robotic nanopositioners, SEM platforms are now capable of precise additive and subtractive fabrication, in-situ manipulation, and real-time characterization at the micro- and nanoscale. These capabilities open new frontiers in fields ranging from nanomaterials research and MEMS/NEMS fabrication to biomedical microrobotics and adaptive sensing platforms. The seminar provides a systematic overview of experimental methods, fabrication strategies, and application scenarios, with an emphasis on understanding how materials can be patterned, sculpted, and assembled under vacuum with nanometer precision. Students will explore a broad array of nanomanufacturing techniques, including: • FIB milling for subtractive nanostructuring • GIS-assisted direct-write deposition for local additive manufacturing • Electromigration-induced material transport • Origami-inspired self-folding microstructures • Lab-on-fiber platforms integrating optics, sensing, and actuation Two in-depth case studies from recent research will be presented: 1. Nanorobotic origami structures fabricated inside SEM using FIB and GIS, enabling the creation of dexterous, self-folding micromanipulators. 2. Liquid metal droplet fabrication using electromigration and FIB sputtering, offering nanometer-scale control for contact angle measurements and soft microactuators. Students will select an individual topic for deeper exploration, which may be theoretical (e.g., modeling of sputtering dynamics, design of MEMS grippers), practical (e.g., concept design for SEM experiments), or even experimental for selected participants. Students are also encouraged to propose their own topics based on their interests. Where possible, hands-on experience can be offered, such as performing nanomanufacturing/nanocharacterization processes under SEM platform or using robotic tools for nano-manipulation tasks. In the second half of the semester, each student will give a presentation or demonstration of their selected topic and will receive feedback on both scientific content and English-language communication. Learning Objectives: • Gain a broad understanding of SEM-based nanomanufacturing tools and processes • Learn to compare and apply additive and subtractive fabrication methods • Analyze current trends in nanorobotics, microfabrication, and integrated platforms • Understand experimental workflows inside a high-vacuum SEM chamber • Develop English-language communication skills in nanotechnology contexts • Strengthen independent research, critical reading, and presentation capabilities	Seminar	-	Dr. Yuning Lei	Master
2.01.530	Introduction to Artificial Intelligence Wednesday, 16:00 - 18:00, Weekly (from 08.04.26) Tuesday, 28.07.26, 08:00 - 10:00 o'clock Tuesday, 28.07.26, 08:00 - 10:00 o'clock Description: This course introduces Artificial Intelligence (AI), exploring its foundations, historical milestones, and real-world applications. Topics include the definition of AI, the Turing Test, Artificial General Intelligence (AGI), and ethical considerations. It covers essential machine learning algorithms like K-Nearest Neighbors (KNN) and K-Means Clustering, evaluation metrics such as accuracy, precision, and recall, as well as deep learning techniques including neural networks, Convolutional Neural Networks (CNN), data augmentation, and dropout. Advanced topics include transformers, sequence learning, large language models (LLMs) like GPT, and prompting strategies for AI agents. Through a mix of theory and hands-on exercises, this course equips students with the knowledge and skills to understand and apply AI technologies effectively.	Lecture	2	Prof. Dr. Oliver Kramer Jill Baumann	Master of Education Bachelor Erweiterungsfach
2.01.369-B	Selected topics in Computer Vision – Practical image processing techniques Friday, 14:00 - 15:30, Fortnightly (from 24.04.26) Description: The functionality of modern computer vision systems—from medical imaging and autonomous driving to industrial inspection and satellite imaging—relies heavily on robust image processing techniques. This seminar focuses on practical image processing techniques using OpenCV, one of the most widely used open-source computer vision libraries. The seminar is designed to equip students with hands-on skills to handle, analyse, and process images. Students will select a topic of interest, either from a provided list or one they propose, and apply OpenCV techniques to a specific microscopy-related task or dataset. There is a possibility to also dive into neural networks for image classification and object detection. Toward the end of the seminar, each student will give a presentation demonstrating their work and share insights gained during the process. Learning Objectives: Acquire knowledge in the field of image processing, including: o Fundamental concepts in digital imaging and image representation, o Core techniques such as feature detection, morphological operations, and segmentation, o Practical applications in microscopy	Seminar	-	Divyang Prakashbhai Rana	Master
2.01.5112	Digitalised Energy System Modeling and Control Wednesday, 10:00 - 12:00, Weekly (from 15.04.26) Friday, 12:00 - 14:00, Weekly (from 17.04.26) Description:	Lecture	4	Prof. Dr. Sebastian Lehnhoff Malin Radtke, M. Sc. Jörg Bremer	Master
2.01.814-A	Advances in Security & Privacy The course times are not decided yet. Description: // Goals of the course /// At the end of the course, students will be able to * analyze the technical merits of specific developments within the field of IT-security, * substantiate their analyses using existing and scientific documented knowledge, * clearly write up those analyses in a concise scientific report, and * further develop an attitude in which being able to clearly explain matters is geared to optimize the quality of feedback. /// Course contents /// The course contents consist of studying and assessing a specific topic from the fields of security and/or privacy. There will be multiple topics, and each topic is to be tackled by an individual student. Students will be handed out material such as scientific articles to help them understand the topic at hand. Part of the course consists of discovering additional material. Students will dig deep into the selected topic. Students will present their analyses and findings in two ways: in a concise scientific report as well as in a 20 min. presentation, which is followed by a discussion and a round of feedback. In the start of the course, all available topics will be introduced to the students so that they can pick a for them suitable topic. /// Assessment /// Students will be assessed on the basis of their written scientific report (high weight), their presentation and consequent discussion (medium to high weight), and the general process (low weight; includes: independence, planning, active involvement, …) /// Topics /// Explainable Machine Learning in Security Attacks on Searchable Encrypted Databases and Countermeasures (Semi-)Automated Security Event Handling in Security Operations Centers Post-Quantum Encryption Algorithms Interplay of Safety and Security Mobile-App Fingerprinting on Encrypted Network Traffic Biometric Template Protection Automated Extraction of Tactics, Techniques, and Procedures from Cyber Threat Reports Your Own Topic More details on the topics will follow.	Seminar	-	Marvin Büchel Prof. Dr. Andreas Peter	Master
2.01.490	Seminar: Concurrency Verification Wednesday, 08.04.26, 16:00 - 18:00 o'clock Description: In this seminar, we will take a look at different techniques for verifying concurrent programs.	Seminar	-	Prof. Dr. Heike Wehrheim Lara Bargmann	Master
2.01.175	Digital Design and Fabrication Thursday, 10:00 - 12:00, Weekly (from 09.04.26) Thursday, 12:00 - 14:00, Weekly (from 09.04.26) Description:	Lecture	4	Prof. Dr. Susanne Boll-Westermann Mikołaj Woźniak Tobias Lunte	Master
2.01.593	Generative Artificial Intelligence (GenAI) The course times are not decided yet. Description: ONLINE	Lecture	-	Prof. Dr. Daniel Sonntag Novruz Mammadli Pratik Sitapara	Master
2.01.492	Advances in Automated Program Verification Tuesday, 07.04.26, 08:00 - 10:00 o'clock Tuesday, 14.07.26, 08:00 - 18:00 o'clock Wednesday, 15.07.26, 08:00 - 18:00 o'clock Description: In this seminar, we will study new developments in the realm of automated program verification techniques. Depending on the participants, we will either focus on methods for reasoning about probabilistic or classical programs (e.g. in Rust).	Seminar	-	Prof. Dr. Christoph Matheja M. Sc. Roberto Pettinau	Master
2.01.462	Cryptography Monday, 16:00 - 18:00, Weekly (from 13.04.26) Thursday, 10:00 - 12:00, Weekly (from 23.04.26) Description:	Lecture	2	Valentin Reyes Häusler Prof. Dr. Andreas Peter	Master of Education Erweiterungsfach Master
2.01.5460	Applied AI - Multimodal-Multisensor Interfaces 3: Language Processing, Software, Commercialization, and Emerging Directions Wednesday, 22.04.26, 12:00 - 13:00 o'clock Description: This third seminar takes the contents of the first two seminars—namely, the motivations, foundational concepts, basic modality combinations, component analyses, and recognition and fusion techniques—to the next level. MMI 3 discusses how to design and build functioning multimodal-multisensor systems that can sustain real-world use. This seminar is most appropriate for graduate students and of primary interest to students studying computer science and information technology, human-computer interfaces, mobile and ubiquitous interfaces, affective and behavioral computing, machine learning, and related multidisciplinary majors. It is very useful if you want to work on practical applications, transfer of AI technology to application domains such as medicine and healthcare, and industrial prototypes. Afterward, students might engage in a hands-on project in which they design, build, and evaluate the performance of a multimodal system in our project group MMI II (https://elearning.uni-oldenburg.de/dispatch.php/course/details?sem_id=098bd500a63e723551364c7f921755b5&again=yes). Central part of the seminar is the reference book "The Handbook of Multimodal-Multisensor Interfaces: Language Processing, Software, Commercialization, and Emerging Directions - Volume 3" (https://dl.acm.org/doi/book/10.1145/3233795). At the beginning there will be an introduction to the subject. Everyone will receive a chapter, for which a presentation and a written elaboration (5-10 pages) are to be prepared. Contact: Rida Saghir, rida.saghir@uni-oldenburg.de	Seminar	-	Novruz Mammadli Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag	Master
2.01.810-A	Advanced Methods for Verifiable Computation The course times are not decided yet. Description: // Goals of the course /// At the end of the course, students will be able to * analyze the technical merits of specific developments regarding verifiable computation methods in lattice based cryptography. * substantiate their analyses using existing and scientific documented knowledge, * clearly write up those analyses in a concise scientific report, and * further develop an attitude in which being able to clearly explain matters is geared to optimize the quality of feedback. /// Course contents /// The course contents consist of studying and assessing a specific method of verifiable computation for lattice based cryptography. Each available topic is to be tackled by an individual student. For this purpose students will be provided with material such as scientific articles to help them understand the topic at hand. Part of the course consists of discovering additional material. Students will dig deep into the selected topic. Finally, students will present their analyses and findings in two ways: in a concise scientific report as well as in a 20 min. presentation, which is followed by a discussion and a round of feedback. At the beginning of the course, all available topics will be introduced to the students so that they can pick a topic suitable for them. /// Assessment /// Students will be assessed on the basis of their written scientific report (high weight), their presentation and consequent discussion (medium to high weight), and the general process (low weight; includes: independence, planning, active involvement, …) /// Requirements /// Students are expected to have knowledge on secure multi-party and outsoutced computation. Succesful completion of a prior seminar 'Computing on Encrypted Data' or 'Advances in Security & Privacy' is expected in addition to the module 'Introduction to IT-Security'. /// Topics /// * Verifiable Fully Homomorpic Encryption; * Zero-knowledge proofs over polynomial rings; * Theory of Verifability; * Distributed Verifiability; * Your Own Topic; More details on the topics will follow.	Seminar	-	Valentin Reyes Häusler Prof. Dr. Andreas Peter	Master
2.01.814-B	Computing on Encrypted Data The course times are not decided yet. Description: // Goals of the course /// At the end of the course, students will be able to * analyze the technical merits of specific developments regarding secure computation methods on encrypted data, * substantiate their analyses using existing and scientific documented knowledge, * clearly write up those analyses in a concise scientific report, and * further develop an attitude in which being able to clearly explain matters is geared to optimize the quality of feedback. /// Course contents /// The course contents consist of studying and assessing a specific method of secure computation on encrypted data. Each available topic is to be tackled by an individual student. For this purpose students will be provided with material such as scientific articles to help them understand the topic at hand. Part of the course consists of discovering additional material. Students will dig deep into the selected topic. Finally, students will present their analyses and findings in two ways: in a concise scientific report as well as in a 20 min. presentation, which is followed by a discussion and a round of feedback. At the beginning of the course, all available topics will be introduced to the students so that they can pick a topic suitable for them. /// Assessment /// Students will be assessed on the basis of their written scientific report (high weight), their presentation and consequent discussion (medium to high weight), and the general process (low weight; includes: independence, planning, active involvement, …) /// Topics /// * Hardware Acceleration for Homomorpic Encryption; * Funtional Encryption; * NTRU-based Homomorphic Encryption; * Threshold and Multiparty Homomorphic Encryption; * Hybrid Homomorphic Encryption; * Functional Secret Sharing; * Your Own Topic; More details on the topics will follow.	Seminar	-	Valentin Reyes Häusler Prof. Dr. Andreas Peter	Master
2.01.900-B	Projektgruppe Artificial Intelligence & Natural Language Processing The course times are not decided yet. Description:	Practical training	-	Prof. Dr. Daniel Sonntag Hannes Kath	Master
2.01.338	Engineering Self-Adaptive Systems Wednesday, 08:00 - 10:00, Weekly (from 08.04.26) Friday, 10:00 - 12:00, Weekly (from 10.04.26) Description: Self-adaptive systems adapt their behaviour or their architecture to changing conditions in their operating context. They provide the flexibility necessary for coping with design time uncertainties. In this course you will learn about: - the motivation for self-adaptation - the basic principles and conceptual model of self-adaptation - how to engineer self-adaptive software systems - how to ensure quality of those systems - the notion of uncertainty in self-adaptive systems and how to tame it - typical application domains for self-adaptive systems	Lecture	4	M. Sc. Ali Torbati Prof. Dr. Verena Klös	Master
2.01.369-A	Selected topics in nanomechanics and the mechanical characterization of nanomaterials using microscopy The course times are not decided yet. Description: The functionality of biomimetic reversable adhesives, ultra-high strength nanocomposites, piezoelectric nanogenerators, electromechanical contact switches, mechanical resonators, as well as ultra-sensitive force and chemical sensors is dependent on nanomechanical phenomena. To experimentally investigate nanomechanical phenomena, nanorobotics and microscopy tools are combined and exploited. A variety of topics within the field of nanomechanics and related experimental methods and tools are presented in an introductory lecture. Students select a topic that they are most interested in to carry out individual work. Topics can be more theoretically or practically orientated depending on the curiosity of the student. Students can also propose their own topics. Students can also be provided with the opportunity to conduct laboratory work, including carrying out nanomanipulation using optical or scanning electron microscopes. In the second half of semester, each student will give a lecture or presentation on their selected topic, and will be provided feedback on both their content and communication skills. Learning objectives: • Acquire knowledge in the field of nanomechanics, including: o fundamental concepts in the mechanic properties of materials, o the advantages, challenges, and application of nanomaterials, o microscopy and nanohandling basics and their application towards studying the mechanics of nanomaterials o insights into the state of the art in nanomechanics research. • Further develop research and communication skills through self-directed reading and presentations.	Seminar	-	Dr. James Mead	Master
2.01.100	Human-Computer Interaction Wednesday, 10:00 - 12:00, Weekly (from 08.04.26) Friday, 10:00 - 12:00, Weekly (from 10.04.26) Description:	Lecture	4	Prof. Dr. Susanne Boll-Westermann Tobias Lunte Mikołaj Woźniak Pavel Karpashevich	Master
2.01.804	Project "Research-Based Learning" - Why doesn't my robot load the dishwasher? Tuesday, 14:00 - 16:00, Weekly (from 21.04.26) Tuesday, 14.04.26, 16:00 - 18:00 o'clock Description: Develop a robot that loads the dishwasher or explains why he doesn't: Topics: Embedded Systems, object detection, robotics, explainability	Lecture	2	Prof. Dr. Verena Klös Cong Wang	Bachelor Erweiterungsfach Master of Education
2.01.652	Anwendungssysteme in Industrieunternehmen The course times are not decided yet. Description: Wird als ATLANTIS E-Learning Modul ausschliesslich an Studenten anderer Universitäten angeboten. Oldenburger Studenten können dafür das inhaltlich gleiche Modul “Produktionsorientierte Wirtschaftsinformatik” im Wintersemester belegen	Lecture	-	Dr.-Ing. Sovanna Chhoeung	Master
2.01.369	Selected Topics in Microwave-Microscopy The course times are not decided yet. Description:	Seminar	-	Dr.-Ing. Muhammad Yasir	Master
2.01.607	Business Intelligence II The course times are not decided yet. Description: VL/Ü	Lecture	-	Dr.-Ing. Andreas Solsbach Prof. Dr. Jorge Marx Gómez Viktor Dmitriyev	Master
2.01.813	Safety and Explainability of ML Wednesday, 14:00 - 16:00, Weekly (from 08.04.26) Description: This seminar addresses two critical challenges in modern machine learning: ensuring that models behave reliably in real-world scenarios, and making their decisions understandable to humans. We explore techniques for analyzing and improving the safety of machine learning systems, including robustness to adversarial inputs, uncertainty estimation, and formal verification. In parallel, we examine methods for explainability, such as feature attribution (e.g., SHAP, LIME), counterfactual explanations, and surrogate models. The seminar includes presentations and discussions based on recent research papers in both areas. Students will gain familiarity with state-of-the-art methods, evaluation criteria, and open challenges, particularly in high-stakes domains such as autonomous systems, healthcare, and finance. The seminar is ideal for students interested in trustworthy AI, applied machine learning, formal methods, or human-centered AI.	Seminar	2	Prof. Dr. Chih-Hong Cheng	Master
2.01.591b	Smart Grid Research Thursday, 10:00 - 12:00, Weekly (from 16.04.26) Description:	Lecture	2	Prof. Dr. Sebastian Lehnhoff Malin Radtke, M. Sc. Jörg Bremer	Bachelor Master Master of Education
2.01.AM-2	Oberseminar Applied Artificial Intelligence Tuesday, 08:00 - 10:00, Weekly (from 07.04.26) Description: Your Advisor and Your Committee In order to write a bachelor’s or master’s thesis you must find a member of the IML lab who is willing to be your thesis advisor. You propose your thesis topic together with your advisor to Prof. Sonntag as the first reviewer in your committee. How Long Should it Be? How Long Does it Take? A bachelor’s thesis is generally 20-40 pages, not including the bibliography. A master’s thesis is generally 40-80 pages, not including the bibliography. However, the length will vary according to the topic and the method of analysis, so the appropriate length will be determined by you, your advisor, and your committee. Students who write a master’s thesis generally do so over two semesters, bachelor’s one semester. More information: https://iml.dfki.de/teaching/writing-a-thesis/	Seminar	2	Michael Barz, M. Sc. Hannes Kath Prof. Dr. Daniel Sonntag Rida Saghir	Master of Education Bachelor Master
2.01.515	Intelligent Energy Systems The course times are not decided yet. Description: Modern power grids face a multitude of challenges: A high share of renewables means a more sophisticated management of real power demand and supply, ancillary services are provided in an ever more decentralized manner, and power grids must become resilient instead of just being robust. Agent systems have established themselves as methodology for a decentralized and resilient operation of modern power grids. Especially learning agents based on Deep Reinforcement Learnings can react to unforseen events and find good strategies even in complex situations. In this lecture, we will introduce an approach for flexibility modelling as a way to provide an agent's view of the world, and will extensively concern ourselves with the application of Deep Reinforcement Learning in power grids, including approaches to explainability and learning from domain knowledge (offline learning).	Lecture	-	Dr.-Ing. Eric Veith Jörg Bremer	Master
2.01.308	Mikrorobotik II Wednesday, 14:00 - 16:00, Weekly (from 08.04.26) Thursday, 14:00 - 16:00, Weekly (from 09.04.26) Description:	Lecture	2	Prof. Dr. Sergej Fatikow Dr. James Mead	Master
2.01.809-B	Selected Topics in IT-Security Thursday, 14:00 - 16:00, Weekly (from 09.04.26) Description: /// Goals of the course /// At the end of the course, students will be able to * analyze the technical merits of specific developments within the field of IT-security, * substantiate their analyses using existing and scientific documented knowledge, * clearly write up those analyses in a concise scientific report, and * further develop an attitude in which being able to clearly explain matters is geared to optimize the quality of feedback. /// Course contents /// The course contents consist of studying and assessing a specific topic in the field of IT-security. There will be multiple topics, and each topic is to be tackled by an individual student. Students will be handed out material such as scientific articles to help them understand the topic at hand. Part of the course consists of discovering additional material. Students will dig deep into the selected topic. Students will present their analyses and findings in two ways: in a concise scientific report as well as in a 20 min. presentation, which is followed by a discussion and a round of feedback. In the start of the course, all available topics will be introduced to the students so that they can pick a for them suitable topic. /// Assessment /// Students will be assessed on the basis of their written scientific report (high weight), their presentation and consequent discussion (medium to high weight), and the general process (low weight; includes: independence, planning, active involvement, …) /// Topics /// * Malicious software * Security operations centers and their performance * Weaknesses of the RSA cryptosystem * Zero-knowledge proofs (ZKPs) * Online tracking methods and countermeasures * Privacy in instant messaging * Privacy metrics and ways to achieve certain privacy levels * Your own topic More details will follow.	Seminar	2	Prof. Dr. Andreas Peter	Bachelor
2.01.815	Machine Learning in Security The course times are not decided yet. Description: // Goals of the course /// At the end of the course, students will be able to * analyze the technical merits of specific developments regarding the topic of machine learning in the field of IT-security, * substantiate their analyses using existing and scientific documented knowledge, * clearly write up those analyses in a concise scientific report, and * further develop an attitude in which being able to clearly explain matters is geared to optimize the quality of feedback. /// Course contents /// The course contents consist of studying and assessing selected methods in machine learning in an IT-security context. Each available topic is to be tackled by an individual student. For this purpose students will be provided with material such as scientific articles to help them understand the topic at hand. Part of the course consists of discovering additional material. Students will dig deep into the selected topic. Finally, students will present their analyses and findings in two ways: in a concise scientific report as well as in a 20 min. presentation, which is followed by a discussion and a round of feedback. At the beginning of the course, all available topics will be introduced to the students so that they can pick a topic suitable for them. /// Assessment /// Students will be assessed on the basis of their written scientific report (high weight), their presentation and consequent discussion (medium to high weight), and the general process (low weight; includes: independence, planning, active involvement, …) /// Topics /// More details on the topics will follow.	Seminar	-	Marvin Büchel Prof. Dr. Andreas Peter	Master
2.01.810	Explainable Artificial Intelligence - Introduction and Application Design The course times are not decided yet. Description: This course combines theoretical foundations from the field of Explainable Artificial Intelligence (XAI) with practical implementations for real-world problems. The course is stuctured in 4 parts: Part I includes the research of the theoretical background of Explainable Artificfial Intelligence (XAI). Part II is a 1-week programming block seminar covering the basics of XAI. In Part III, you will build and evaluate your own real-world XAI application and write a term paper. Part IV is a presentation and feedback session. Please download the instructions for the assignment to get a detailed overview of the course structure. This module will be held in cooperation with students from the Ruhr University Bochum (Prof. Dr. Christian Meske). The entire course takes place online. All course materials will be made available in the cloud storage of the Ruhr Universität Bochum. To access them, please create an account by following the steps below: 1. https://moodle.ruhr-uni-bochum.de/login/index.php 2. create a new account ("Neues Konto anlegen") 3. accept the "Terms of Use" 4. accept the "Privacy Policy" 5. fill in the document 5.1 Reason for creating an account Participation in a course (study outside the RUB) ("Grund für die Erstellung des Kontos: Teilnahme an einer Lehrveranstaltung (Studium außerhalb der RUB)") 6. confirm your email address via the link in RUB Moodle: Confirmation of access (mail may take a few minutes) 7. search for the course: (Name and PW will be announced soon)	Seminar	-	Christoph Johns Hannes Kath Prof. Dr. Daniel Sonntag Pratik Sitapara	Master
2.01.5118	Decentralised Nonlinear Model-Based Control in Digitalised Energy Systems Monday, 08:00 - 10:00, Weekly (from 13.04.26) Monday, 10:00 - 12:00, Weekly (from 13.04.26) Description: 1. Fundamentals of control-oriented modeling 2. Special properties of nonlinear control systems · Finite escape time · Chaos · Limit cycles · Equilibria 3. Stability properties/ Stability analysis · Local vs. global stability · Lyapunov methods · Stability of limit cycles · Criteria for the proof of instability 4. Nonlinear control design · Control Lyapunov functions · Backstepping control · Feedback linearization · Flatness-based control 5. Nonlinear observer synthesis	Lecture	4	Prof. Dr.-Ing. habil. Andreas Rauh Marit Lahme Jelke Wibbeke, M. Sc. Dr.-Ing. Friederike Bruns	Master
2.01.592	Advanced Topics in Applied Artificial Intelligence Tuesday, 07.04.26, 08:00 - 10:00 o'clock Monday, 04.05.26, 08:00 - 12:00 o'clock Tuesday, 05.05.26, 08:00 - 12:00 o'clock Wednesday, 06.05.26, 08:00 - 12:00 o'clock Thursday, 07.05.26, 08:00 - 12:00 o'clock Friday, 08.05.26, 08:00 - 12:00 o'clock Tuesday, 25.08.26, 08:00 - 18:00 o'clock Description: This block seminar will explore advanced topics in artificial intelligence with a focus on embedding spaces, transfer learning, multimodal retrieval, and active learning. In addition to theoretical foundations, the course includes hands-on practical exercises, implementation of small projects, and interactive sessions designed to reinforce understanding through practical applications.	Seminar	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag Thiago Gouvea	Master
2.01.591a	Resilient operation of future power grids Thursday, 12:00 - 14:00, Weekly (from 09.04.26) Description: Angestrebte Lernergebnisse: Students gain an overview of the structure and operation of the electricity system with a focus on Germany/Europe. They learn how the resilient operation of future electricity grids with a high share of electricity from renewable sources can be ensured from basics to real operation. Another focus is on acquiring basic knowledge of power grid modelling and insights into the laboratory operation of power grid simulation. Within the lecture, examples are simulated with Matlab Simulink and other simulation tools. Students also gain insights into current research projects and real-life applications. Inhalt Overview of the structure of the current and future electricity system Ensuring frequency stability including advanced technologies Voltage stability in distribution grid with new approaches (also AI-based) Grid operation with flexibilities - communication and operation Resilience considerations Monitoring and data analysis – examples from a real district energy system Examples of dynamic electricity grid and energy system simulations Hardware emulation and experiments with real power We will also work with Matlab and other simulation tools Medienformen Blackboard, beamer presentation Literatur Selected articles from scientific journals and overview articles	Lecture	2	Prof. Dr.-Ing. habil. Andreas Rauh Dr. Karsten von Maydell	Master
2.01.108	Requirements Engineering and Management Wednesday, 12:00 - 14:00, Weekly (from 08.04.26) Thursday, 12:00 - 14:00, Weekly (from 09.04.26) Description: The basic terms and concepts of requirements analysis are taught, and methods and techniques of requirements elicitation and management are discussed and practically tested. Topics covered include: -Need for requirements elicitation and requirements management. -requirements engineering in the software development process (in the waterfall model, in the unified process, in agile development) -Requirements engineering process (participants, documents, activities) -Understand application domain (create vision, document system environment, create domain model, identify use cases) -Evoke requirements (functional and non-functional requirements, gather requirements, document requirements, validate requirements, negotiate requirements) -Manage requirements	Lecture	4	Prof. Dr. Andreas Winter	Master
2.01.5124	Research Project Digitalised Energy Systems The course times are not decided yet. Description:	Practical training	-	Prof. Dr.-Ing. habil. Andreas Rauh Prof. Dr. Sebastian Lehnhoff Prof. Dr. Astrid Nieße Jörg Bremer Dr.-Ing. Eric Veith	Master
2.01.965	STS Eng.: Systems Engineering Friday, 12:00 - 14:00, Weekly (from 10.04.26) Description: Das Modul besteht aus einer Vorlesung und einem Übungsteil: Vorlesung: Einführung in die Konzepte von Systemen, Methodologien und Methoden des Systems Engineering. Besonderes Augenmerk wird auf die Verwendung von modellbasierten Methoden gelegt. Übungen: Eigene Entwurfserfahrungen unter Verwendung von Engineering-Methoden und -Werkzeugen.	Lecture	2	Prof. Dr. Martin Georg Fränzle M. Sc. Rabeaeh Kiaghadi	Master
2.01.5456	Applied AI - Multimodal-Multisensor Interfaces 1: Foundations, User Modeling, and Common Modality Combination Wednesday, 22.04.26, 10:00 - 11:00 o'clock Description: We look at relevant theory and neuroscience foundations for guiding the development of high-performance systems. We discuss approaches to user modeling, interface design that supports user choice, synergistic combination of modalities with sensors, and blending of multimodal input and output. We also highlight an in-depth look at the most common multimodal-multisensor combinations- for example, touch and pen input, haptic and non-speech audio output, and speech co-processed with visible lip movements, gaze, gestures, or pen input. A common theme throughout is support for mobility and individual differences among users-including the world's rapidly growing population of seniors. This seminar would be most appropriate for graduate students, and of primary interest to students studying computer science and information technology, human–computer interfaces, mobile and ubiquitous interfaces, and related multidisciplinary majors. Central part of the seminar is the reference book "The Handbook of Multimodal-Multisensor Interfaces: Signal Processing, Architectures, and Detection of Emotion and Cognition - Volume 1" (https://dl.acm.org/doi/book/10.1145/3015783). At the beginning there will be an introduction to the subject. Everyone will receive a chapter, for which a presentation and a written elaboration (5-10 pages) are to be prepared. Contact: rida.saghir@uni-oldenburg.de	Seminar	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag	Master
2.01.481	Software Analysis Thursday, 14:00 - 16:00, Weekly (from 09.04.26) Monday, 10:00 - 12:00, Weekly (from 13.04.26) Description: Software analyses extract facts about programs from source code. Such facts can be employed by compilers to optimize programs during compilation, but can also be used to verify correctness of programs. In this course, we will get to know different analysis techniques and also implement some ourselves.	Lecture	4	Prof. Dr. Heike Wehrheim Nicola Anna Thoben Rohith Kumar Shanmuganathan	Master
2.01.5106	Optimal and Model-Predictive Control Tuesday, 12:00 - 14:00, Weekly (from 07.04.26) Thursday, 08:00 - 10:00, Weekly (from 09.04.26) Description: 1. Parameter optimization · Unconstrained optimisation · Optimisation under equality/ inequality constraints 2. Dynamic optimisation (structural optimi-sation) · Bellman’s optimality principle · Maximum principle of Pontryagin · Special optimisation problems: Mini-mum time problems, minimum energy, LQR 3. Linear model-predictive control 4. Nonlinear model-predictive control 5. Receding horizon state estimation	Lecture	4	Prof. Dr.-Ing. habil. Andreas Rauh Dr.-Ing. Friederike Bruns Jelke Wibbeke, M. Sc. Marit Lahme	Master
2.01.5122	Learning-Based Control in Digitalised Energy Systems Tuesday, 14:00 - 16:00, Weekly (from 07.04.26) Tuesday, 16:00 - 18:00, Weekly (from 07.04.26) Description: 1. Iterative learning control (ILC) · Fundamental 2D system structures · Stability criteria · Selected optimization approaches 2. Data-driven neural network model-ing vs. first-principle modeling · Static function approximations · NARX modeling 3. Design of neural network-based controllers 4. Stability of neural network-based controllers	Lecture	4	Prof. Dr.-Ing. habil. Andreas Rauh Marit Lahme Dr.-Ing. Friederike Bruns Jelke Wibbeke, M. Sc.	Master
2.01.5458	Applied AI - Multimodal-Multisensor Interfaces 2: Signal Processing, Architectures, and Detection of Emotion and Cognition Wednesday, 22.04.26, 11:00 - 12:00 o'clock Description: We begin with multimodal signal processing, architectures, and machine learning. It includes recent deep-learning approaches for processing multisensorial and multimodal user data and interaction, as well as context-sensitivity. A further highlight is processing of information about users' states and traits, an exciting emerging capability in next-generation user interfaces. We discuss real-time multimodal analysis of emotion and social signals from various modalities and perception of affective expression by users. Then we discuss multimodal processing of cognitive state using behavioral and physiological signals to detect cognitive load, domain expertise, deception, and depression. This collection of chapters provides walk-through examples of system design and processing, information on tools and practical resources for developing and evaluating new systems, and terminology, and tutorial support for mastering this rapidly expanding field. Finally, we look at experts' exchange views on the timely and controversial challenge topic of multimodal deep learning. The discussion focuses on how multimodal-multisensor interfaces are most likely to advance human performance during the next decade. This seminar is most appropriate for graduate students and of primary interest to students studying computer science and information technology, human-computer interfaces, mobile and ubiquitous interfaces, affective and behavioral computing, machine learning, and related multidisciplinary majors. Central part of the seminar is the reference book "The Handbook of Multimodal-Multisensor Interfaces: Signal Processing, Architectures, and Detection of Emotion and Cognition - Volume 2" (https://dl.acm.org/doi/book/10.1145/3107990). At the beginning there will be an introduction to the subject. Everyone will receive a chapter, for which a presentation (30 min. + 30 min. discussion) and a written elaboration (5-10 pages) are to be prepared. Contact: Hannes Kath, hannes.kath@uni-oldenburg.de	Seminar	-	Hannes Kath Rida Saghir Prof. Dr. Daniel Sonntag	Master
2.01.812	Theoretical Foundations of AI Safety Wednesday, 10:00 - 12:00, Weekly (from 08.04.26) Description: This master-level seminar explores the theoretical principles underlying the safety, robustness, and alignment of modern AI systems. Students will engage with cutting-edge research on adversarial robustness, distribution shift, formal verification of neural networks, safe reinforcement learning, and foundational alignment theory. Each week focuses on a topic, with students leading presentations and discussions to critically analyze assumptions, guarantees, and limitations of current approaches. The seminar emphasizes rigorous reasoning, mathematical foundations, and formal models of safety-relevant behavior. Students will gain a deep understanding of the theoretical challenges in making learning-enabled autonomous systems reliable, predictable, and certifiably safe. We expect the students to deliver a 1.5~2-hour lecture on a specific topic, making minimal assumptions about participants' knowledge of linear algebra, probability, and statistics. After the lecture, the participants can fully understand the underlying principles while using examples serving as intuitions. This course is suitable for those who wish to enter the frontier of artificial intelligence research or join leading industrial labs. The solid mathematics and analytical skills will be a great plus for your future career.	Seminar	2	Prof. Dr. Chih-Hong Cheng	Master
2.01.359	Project "Research-Based Learning" - Why doesn't my robot load the dishwasher? Tuesday, 14:00 - 16:00, Weekly (from 28.04.26) Tuesday, 14.04.26, 16:00 - 18:00 o'clock Description: Develop a robot that loads the dishwasher or explains why he doesn't: Topics: Embedded Systems, object detection, robotics, explainability	Lecture	2	Prof. Dr. Verena Klös Cong Wang	Master
2.01.5128	AI in Energy Systems Monday, 14:00 - 16:00, Weekly (from 13.04.26) Description:	Seminar	2	Jörg Bremer	Master
46 Seminars