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 2025 22 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
2.01.814	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
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
2.01.369	Selected Topics in Microwave-Microscopy and -Communication Systems Thursday: 08:00 - 10:00, weekly (from 10/04/25) Description:	Seminar	2	Dr.-Ing. Muhammad Yasir	Master
2.01.809	Selected Topics in IT-Security Thursday: 14:00 - 16:00, weekly (from 10/04/25) 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
2.01.815	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
2.01.586	Fitness Landscape Analysis Thursday: 10:00 - 12:00, weekly (from 10/04/25) Description:	Seminar	2	Jörg Bremer	Master
2.01.490	Logical Methods in AI Verification The course times are not decided yet. Description: In this seminar, we will take a look at logical methods for AI verification and explanation. In this seminar, we will take a look at logical methods for AI verification and explanation.	Seminar	-	Prof. Dr. Heike Wehrheim	Master
2.01.5450	Current topics in self-supervised and label-efficient learning Tuesday: 16:00 - 18:00, weekly (from 08/04/25) Description: This seminar will cover current approaches to improve the label-efficiency of machine learning systems in different application domains such as computer vision, speech and natural language processing. A particular focus will lie on self-supervised learning but we will also cover aspects of self-training and weak supervision. This seminar will cover current approaches to improve the label-efficiency of machine learning systems in different application domains such as computer vision, speech and natural language processing. A particular focus will lie on self-supervised learning but we will also cover aspects of self-training and weak supervision.	Seminar	2	Prof. Dr. Nils Strodthoff Tiezhi Wang	Master
2.01.5128	AI in Energy Systems Monday: 14:00 - 16:00, weekly (from 07/04/25) Description:	Seminar	2	Jörg Bremer	Master
2.01.180	Seminar Smart Data and Internet of Things Wednesday: 10:00 - 12:00, weekly (from 09/04/25) 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
2.01.536	Deep Learning Dates on Monday, 22.09.2025 - Friday, 26.09.2025, Monday, 29.09.2025 - Tuesday, 30.09.2025 10:00 - 18:00 Description: This course builds on the foundations laid in “Introduction to AI” and offers a deeper dive into core machine learning and deep learning methods. Students will explore classical approaches such as Support Vector Machines (SVM), as well as modern deep learning architectures including Convolutional Neural Networks, ResNet, and Autoencoders. The course is further enriched by an introduction to Evolution Strategies, linking learning with optimization. This course builds on the foundations laid in “Introduction to AI” and offers a deeper dive into core machine learning and deep learning methods. Students will explore classical approaches such as Support Vector Machines (SVM), as well as modern deep learning architectures including Convolutional Neural Networks, ResNet, and Autoencoders. The course is further enriched by an introduction to Evolution Strategies, linking learning with optimization.	Lecture	-	Prof. Dr. Oliver Kramer	Master
2.01.5458	Applied AI - Multimodal-Multisensor Interfaces 2: Signal Processing, Architectures, and Detection of Emotion and Cognition Dates on Tuesday, 22.04.2025 13:00 - 14:30 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
2.01.592	Advanced Topics in Applied Artificial Intelligence Dates on Monday, 07.04.2025 10:00 - 10:45, Monday, 16.06.2025 - Friday, 20.06.2025 10:00 - 17:00, Wednesday, 03.09.2025 10:00 - 13:00 Description: This block seminar will explore advanced topics in artificial intelligence with a focus on embedding spaces, transfer learning, multimodal retrieval, and active learning. These techniques enable efficient information retrieval, data representation, and performance improvements across multiple domains while including multimedia data such as image, text, and audio data. We will also discuss visualization tools for embedding spaces and interpreting model outputs. This block seminar will explore advanced topics in artificial intelligence with a focus on embedding spaces, transfer learning, multimodal retrieval, and active learning. These techniques enable efficient information retrieval, data representation, and performance improvements across multiple domains while including multimedia data such as image, text, and audio data. We will also discuss visualization tools for embedding spaces and interpreting model outputs.	Seminar	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag Thiago Gouvea	Master
2.01.184	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	-	Marvin Büchel Prof. Dr. Andreas Peter	Master
2.01.5460	Applied AI - Multimodal-Multisensor Interfaces 3: Language Processing, Software, Commercialization, and Emerging Directions Dates on Tuesday, 22.04.2025 13:00 - 14:30 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 (30 min. + 30 min. discussion) 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 (30 min. + 30 min. discussion) 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	Master
2.01.800-E	Proseminar Smart Data Interoperability Wednesday: 10:00 - 12:00, weekly (from 09/04/25) Description:	Seminar	2	Prof. Dr. Andreas Winter Dr. rer. nat. Christian Schönberg	Bachelor Master of Education
2.01.AM-2	Oberseminar Applied Artificial Intelligence Tuesday: 08:00 - 10:00, weekly (from 08/04/25) 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
2.01.5124	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	Master
2.01.5454	Current Topics in Artificial Intelligence for Health Friday: 10:00 - 12:00, weekly (from 11/04/25) Description: This seminar is supposed to cover current publications and/or research topics in the domain of machine learning with particular regard to applications in the health domain. This includes topics with a strong methodological focus (such as self-supervised learning, quality criteria for ML algorithms such as interpretability/uncertainty quantification) but also medical application topics. This seminar is supposed to cover current publications and/or research topics in the domain of machine learning with particular regard to applications in the health domain. This includes topics with a strong methodological focus (such as self-supervised learning, quality criteria for ML algorithms such as interpretability/uncertainty quantification) but also medical application topics.	Seminar	2	Prof. Dr. Nils Strodthoff	Master
2.01.369-A	Selected topics in nanomechanics and the mechanical characterization of nanomaterials using microscopy Wednesday: 08:00 - 10:00, weekly (from 09/04/25) 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
2.01.810	Explainable Artificial Intelligence - Introduction and Application Design Dates on Tuesday, 22.04.2025 16:15 - 17:30, Monday, 25.08.2025 - Friday, 29.08.2025 09:00 - 18:00, Tuesday, 30.09.2025 09:00 - 13:00 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) 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	-	Hannes Kath Prof. Dr. Daniel Sonntag	Master
2.01.5456	Applied AI - Multimodal-Multisensor Interfaces 1: Foundations, User Modeling, and Common Modality Combination Dates on Tuesday, 22.04.2025 13:00 - 14:30 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 (30 min. + 30 min. discussion) and a written elaboration (5-10 pages) are to be prepared. Contact: Ilira Troshani, ilira.troshani@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 (30 min. + 30 min. discussion) and a written elaboration (5-10 pages) are to be prepared. Contact: Ilira Troshani, ilira.troshani@uni-oldenburg.de	Seminar	-	Rida Saghir Hannes Kath Prof. Dr. Daniel Sonntag	Master
22 Seminars