Veranstaltungsverzeichnis

Department of Computing Science

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

Winter semester 2025/2026 29 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
2.01.962b	CS4Science - Tutorial B - in English Thursday: 14:00 - 16:00, weekly (from 16/10/25) Description: This cource introduces basic concepts of Computer Science and also a short introduction to programming in the programming language Python. This cource introduces basic concepts of Computer Science and also a short introduction to programming in the programming language Python.	Exercises	2	Dr. Ute Vogel-Sonnenschein	Master Bachelor
2.01.-CAUSE	Seminar of the RTN CAUSE Wednesday: 10:00 - 12:00, weekly (from 06/11/24) Description: The seminar is dedicated to the ongoing scientific exchange and cooperation of the memvers of the RTN CAUSE at Oldenburg. 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
2.01.5460	Applied AI - Multimodal-Multisensor Interfaces 3: Language Processing, Software, Commercialization, and Emerging Directions The course times are not decided yet. 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 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	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag Novruz Mammadli	Master
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. // 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
2.01.5458	Applied AI - Multimodal-Multisensor Interfaces 2: Signal Processing, Architectures, and Detection of Emotion and Cognition The course times are not decided yet. 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 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	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag	Master
2.01.5452	Current Topics in Uncertainty Quantification for Machine Learning Algorithms Thursday: 10:00 - 12:00, weekly (from 16/10/25) Description: Maschinelle Lernmodelle werden in vielen verschiedenen Kontexten angewendet und zeigen dabei große Leistungsfähigkeit. Ein Aspekt, der oft übersehen wird, ist die Fähigkeit des Modells, auch die (Un-)Sicherheit seiner Vorhersagen zu quantifizieren, was eine entscheidende Information für viele Anwendungsszenarien darstellt. Dieses Seminar wird verschiedene Ansätze für Unsicherheitsquantifizierungsmethoden für Algorithmen des maschinellen Lernens behandeln, insbesondere tiefe neuronale Netzwerke, die von Bayesschen Ansätzen wie Monte-Carlo-Dropout und Deep Ensembles über Kalibrierungsmethoden bis hin zu konformaler Vorhersage reichen. Das Seminar wird in einem Rollenspiel-Format durchgeführt. Teilnehmer bereiten dabei bestimmte Teilaspekte von vorausgewählten Werken aus der Forschungsliteratur vor. Die verschiedenen Informationen werden dann in einem jeweils folgenden Treffen zusammengesetzt und diskutiert. Maschinelle Lernmodelle werden in vielen verschiedenen Kontexten angewendet und zeigen dabei große Leistungsfähigkeit. Ein Aspekt, der oft übersehen wird, ist die Fähigkeit des Modells, auch die (Un-)Sicherheit seiner Vorhersagen zu quantifizieren, was eine entscheidende Information für viele Anwendungsszenarien darstellt. Dieses Seminar wird verschiedene Ansätze für Unsicherheitsquantifizierungsmethoden für Algorithmen des maschinellen Lernens behandeln, insbesondere tiefe neuronale Netzwerke, die von Bayesschen Ansätzen wie Monte-Carlo-Dropout und Deep Ensembles über Kalibrierungsmethoden bis hin zu konformaler Vorhersage reichen. Das Seminar wird in einem Rollenspiel-Format durchgeführt. Teilnehmer bereiten dabei bestimmte Teilaspekte von vorausgewählten Werken aus der Forschungsliteratur vor. Die verschiedenen Informationen werden dann in einem jeweils folgenden Treffen zusammengesetzt und diskutiert.	Seminar	2	Prof. Dr. Nils Strodthoff	Master
2.01.973	Psychological practicum EEG The course times are not decided yet. Description: The aim of the internship is to apply the knowledge from the lecture on Neurophysiology in the lab. For this purpose, the students will record electroencephalograms from human subjects. They will learn how to place electrodes, how to record EEG and how to analyze simple derivatives of EEG such as the event-related potential (ERP). In the Applied Cognitive Neurocognitive Psychology lab interns are closely linked to ongoing research. The research topics in the lab include characterization and decoding of cognitive and emotional states from brain imaging data (fNIRS, fMRI, MEG) and the analysis of mechanisms of auditory processing of speech. In both topical areas we put a methodological emphasis on data driven machine learning techniques to reveal neuronal correlates of internal states and for human state decoding. In collaboration with workgroups from computer science we also work modelling of human cognitive function and integration of information about human cognitive and emotional states into planning strategies for human-cyber-physical systems. The aim of the internship is to apply the knowledge from the lecture on Neurophysiology in the lab. For this purpose, the students will record electroencephalograms from human subjects. They will learn how to place electrodes, how to record EEG and how to analyze simple derivatives of EEG such as the event-related potential (ERP). In the Applied Cognitive Neurocognitive Psychology lab interns are closely linked to ongoing research. The research topics in the lab include characterization and decoding of cognitive and emotional states from brain imaging data (fNIRS, fMRI, MEG) and the analysis of mechanisms of auditory processing of speech. In both topical areas we put a methodological emphasis on data driven machine learning techniques to reveal neuronal correlates of internal states and for human state decoding. In collaboration with workgroups from computer science we also work modelling of human cognitive function and integration of information about human cognitive and emotional states into planning strategies for human-cyber-physical systems.	Practical training	-	Prof. Dr. Christoph Siegfried Herrmann, Dipl.-Ing. Prof. Dr. Jochem Rieger	Master
2.01.369-B	Selected Topics in Microwave-Microscopy Monday: 12:00 - 14:00, weekly (from 13/10/25) Description:	Seminar	2	Dr.-Ing. Muhammad Yasir	Master
2.01.496	Weak Memory Models Dates on Monday, 13.10.2025 14:00 - 16:00, Tuesday, 20.01.2026 16:00 - 18:00 Description: In this seminar, we will study different weak memory models and verification approaches for concurrent programs. In this seminar, we will study different weak memory models and verification approaches for concurrent programs.	Seminar	-	Lukas Panneke Lara Bargmann Prof. Dr. Heike Wehrheim	Master
2.01.963	Lesson for Informatics - Fundamentals of Psychology: Cognition Thursday: 10:00 - 12:00, weekly (from 23/10/25) Description:	Exercises	2	Prof. Dr. Christoph Siegfried Herrmann, Dipl.-Ing. Dr. Seonghun Park	Master
2.01.5456	Applied AI - Multimodal-Multisensor Interfaces 1: Foundations, User Modeling, and Common Modality Combination The course times are not decided yet. 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 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
2.01.652	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 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
2.01.592	Advanced Topics in Applied Artificial Intelligence Dates on Tuesday, 21.10.2025 10:00 - 11:30, Monday, 24.11.2025 - Friday, 28.11.2025 10:00 - 13:30, Tuesday, 03.02.2026 10:00 - 14:00 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. 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
2.01.809	Selected Topics in IT-Security Thursday: 14:00 - 16:00, weekly (from 16/10/25) 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. /// 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
2.01.5124	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 Jens Sager Malin Radtke, M. Sc. Jörg Bremer Prof. Dr. Philipp Staudt	Master
2.01.369-D	Selected topics in Computer Vision – Practical image processing techniques Friday: 14:00 - 15:00, fortnightly (from 07/11/25), A-01 3-325 Friday: 14:00 - 15:00, weekly (from 23/01/26) Friday: 14:00 - 15:00, weekly (from 28/11/25) Friday: 14:00 - 15:00, weekly (from 17/10/25), Introduction Dates on Friday, 31.10.2025 14:00 - 15:00 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 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.AM-2	Oberseminar Applied Artificial Intelligence Tuesday: 08:00 - 10:00, weekly (from 14/10/25) 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/ 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. Ilira Hiller Hannes Kath Prof. Dr. Daniel Sonntag	Master Bachelor Master of Education
2.01.338	Verification and validation of highly automated vehicles Tuesday: 12:00 - 14:00, weekly (from 14/10/25) Thursday: 12:00 - 14:00, weekly (from 16/10/25) Description: The lectures cover recent methods for assuring safety, reliability, and technical trustworthiness of highly automated vehicles. The lectures cover recent methods for assuring safety, reliability, and technical trustworthiness of highly automated vehicles.	Lecture	4	Priv.-Doz. Dr. Hardi Hungar Prof. Dr. Martin Georg Fränzle	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 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
2.01.5130	Socio-technical Energy Systems Wednesday: 12:00 - 14:00, weekly (from 15/10/25) Description:	Seminar	2	Malin Radtke, M. Sc. Jörg Bremer	Master
2.01.420-c	Introduction to IT-Security (Ü) Friday: 14:00 - 16:00, weekly (from 24/10/25) Description:	Exercises	2	Marvin Büchel Prof. Dr. Andreas Peter	Master of Education Bachelor Erweiterungsfach Master
2.01.180	Seminar Smart Data and Internet of Things Wednesday: 10:00 - 12:00, weekly (from 15/10/25) Description: Together with students from TUIT Urgench (Uzbekistan), current issues in the processing of extensive data in the IoT and in smart regions are developed and discussed in a research-oriented manner. Together with students from TUIT Urgench (Uzbekistan), current issues in the processing of extensive data in the IoT and in smart regions are developed and discussed in a research-oriented manner.	Seminar	2	Dr. rer. nat. Christian Schönberg Prof. Dr. Andreas Winter	Master
2.01.368	Microrobotics Selected Topics Tuesday: 16:00 - 18:00, weekly (from 14/10/25) Description: This seminar is an addition to the main lecture series “2.01.208 Mikrorobotik und Mikrosystemtechnik” Topics - Swimming MR - Flying MR - MR for surface locomotion - Gecko MR - Soft MR - On-chip MR - In-vivo MR - Bacteria- and Cell-MR - MR Swarms - Molecular MR This seminar is an addition to the main lecture series “2.01.208 Mikrorobotik und Mikrosystemtechnik” Topics - Swimming MR - Flying MR - MR for surface locomotion - Gecko MR - Soft MR - On-chip MR - In-vivo MR - Bacteria- and Cell-MR - MR Swarms - Molecular MR	Seminar	2	Prof. Dr. Sergej Fatikow	Master
2.01.420-b	Introduction to IT-Security (Ü) Thursday: 14:00 - 16:00, weekly (from 30/10/25) Description:	Exercises	2	Prof. Dr. Andreas Peter Marvin Büchel	Master of Education Bachelor Erweiterungsfach 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. // 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	-	Prof. Dr. Andreas Peter	Master
2.01.800-A	Seminar Smart Data and Internet of Things Wednesday: 10:00 - 12:00, weekly (from 15/10/25) Description: Together with students from TUIT Urgench (Uzbekistan), current issues in the processing of extensive data in the IoT and in smart regions are developed and discussed in a research-oriented manner. Together with students from TUIT Urgench (Uzbekistan), current issues in the processing of extensive data in the IoT and in smart regions are developed and discussed in a research-oriented manner.	Seminar	2	Dr. rer. nat. Christian Schönberg Prof. Dr. Andreas Winter Boburbek Babajonov Prof. Dr. Oybek Allamov	Bachelor Erweiterungsfach Master of Education
2.01.808-D	Smart Grid Research Wednesday: 12:00 - 14:00, weekly (from 15/10/25) Description: *Disclaimer*: The seminar takes place at Industriestraße 11, room I11-1-Meet. If you would like to participate, please join via StudIP and come to the next session on 10/22. Starting with a basic introduction to Smart Grids, participants are familiarized with the objectives, significance, history, and development of Smart Grids. This forms the basis for a deeper understanding of the key technologies and components used in Smart Grids. In another part of the lecture, students learn the basics of research and acquire skills such as efficient reading of scientific publications. To strengthen the practical and current relevance, ongoing research projects related to selected focus topics are presented concurrently. This allows students to gain insights into the latest developments and challenges in the field of Smart Grids. *Disclaimer*: The seminar takes place at Industriestraße 11, room I11-1-Meet. If you would like to participate, please join via StudIP and come to the next session on 10/22. Starting with a basic introduction to Smart Grids, participants are familiarized with the objectives, significance, history, and development of Smart Grids. This forms the basis for a deeper understanding of the key technologies and components used in Smart Grids. In another part of the lecture, students learn the basics of research and acquire skills such as efficient reading of scientific publications. To strengthen the practical and current relevance, ongoing research projects related to selected focus topics are presented concurrently. This allows students to gain insights into the latest developments and challenges in the field of Smart Grids.	Seminar	2	Julia Catharina Heiken, M.Sc. Dr. Ute Vogel-Sonnenschein	Master Bachelor Master of Education
2.01.369-A	Selected topics in nanomechanics and the mechanical characterization of nanomaterials using microscopy Friday: 12:00 - 14:00, weekly (from 17/10/25) 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. 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	2	Dr. James Mead	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. // 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
29 Seminars