Veranstaltungsverzeichnis

Veranstaltungsverzeichnis

Department of Computing Science Click here for PDF-Download

Summer semester 2024 18 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
2.01.591 Smart Grid Research Thursday: 12:00 - 14:00, weekly (from 04/04/24)

Description:
The seminar "Smart Grid Research" covers a wide range of topics in the research area of smart grids. 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 event, students learn the basics of research and acquire skills such as efficiently reading scientific publications. To strengthen the practical and current relevance, current research projects are presented in conjunction with selected focus topics. This allows students to gain insights into the latest developments and challenges in the field of smart grids. The seminar "Smart Grid Research" covers a wide range of topics in the research area of smart grids. 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 event, students learn the basics of research and acquire skills such as efficiently reading scientific publications. To strengthen the practical and current relevance, current research projects are presented in conjunction with selected focus topics. This allows students to gain insights into the latest developments and challenges in the field of smart grids.
Seminar 2 Prof. Dr. Sebastian Lehnhoff
Malin Radtke, M. Sc.
Jörg Bremer
  • Bachelor
  • Master of Education
  • Master
2.01.369-A Selected topics in nanomechanics and the mechanical characterization of nanomaterials using microscopy Thursday: 10:00 - 12:00, weekly (from 04/04/24)

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
2.01.809 Selected Topics in IT-Security Thursday: 14:00 - 16:00, weekly (from 04/04/24)

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:
Lecture - Prof. Dr.-Ing. habil. Andreas Rauh
Prof. Dr. Sebastian Lehnhoff
Prof. Dr. Astrid Nieße
Jörg Bremer
  • Master
2.01.697 Current Issues on Digital Transformation in the Energy Sector and Green Information Systems Tuesday: 08:00 - 10:00, weekly (from 02/04/24)

Description:
In this module, current research topics related to digital transformation in the energy sector and Green Information Systems are taught, and their relevance for both academia and practical applications is discussed. Through the discussion and reflection on various scientific publications in these subject areas, fundamental insights into understanding research findings and methodological competencies are conveyed. Specifically, these contributions cover the following thematic areas (among others): • (New) Business Models in the Energy Sector • Acceptance and (Non-)Utilization of Sustainable Technologies • Digitalization of Energy Research • Research Data Management in the Energy Sector • Open Science in Energy Research Subject Competencies Students: • are able to comprehend works in the mentioned area and thus can reflect on the current state of research in this field. Methodological Competencies Students: • can understand and discuss scholarly works in the context of the topic. Social Competencies Students: • collaborate in small groups (or individually) to develop an understanding as well as possible further research approaches with appropriate research methodologies related to given scholarly works in the field. • discuss their own understanding and research approaches with others. • reflect on the solutions of fellow students in a constructive manner. Self-Competencies Students: • assess scientific developments for their relevance to practitioners. • identify potential topics for further scholarly works, such as the master's thesis. In this module, current research topics related to digital transformation in the energy sector and Green Information Systems are taught, and their relevance for both academia and practical applications is discussed. Through the discussion and reflection on various scientific publications in these subject areas, fundamental insights into understanding research findings and methodological competencies are conveyed. Specifically, these contributions cover the following thematic areas (among others): • (New) Business Models in the Energy Sector • Acceptance and (Non-)Utilization of Sustainable Technologies • Digitalization of Energy Research • Research Data Management in the Energy Sector • Open Science in Energy Research Subject Competencies Students: • are able to comprehend works in the mentioned area and thus can reflect on the current state of research in this field. Methodological Competencies Students: • can understand and discuss scholarly works in the context of the topic. Social Competencies Students: • collaborate in small groups (or individually) to develop an understanding as well as possible further research approaches with appropriate research methodologies related to given scholarly works in the field. • discuss their own understanding and research approaches with others. • reflect on the solutions of fellow students in a constructive manner. Self-Competencies Students: • assess scientific developments for their relevance to practitioners. • identify potential topics for further scholarly works, such as the master's thesis.
Seminar 2 Dr. Oliver Werth
  • 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 (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
Ilira Troshani
Hannes Kath
Prof. Dr. Daniel Sonntag
  • Master
2.01.AM-56 Oberseminar Applied Artificial Intelligence The course times are not decided yet.
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 - Michael Barz, M. Sc.
Bengt Lüers
Prof. Dr. Daniel Sonntag
Ilira Troshani
  • Bachelor
  • Master of Education
  • Master
2.01.369 Selected Topics in Microwave-Microscopy and -Communication Systems Wednesday: 10:00 - 12:00, weekly (from 03/04/24)

Description:
Seminar 2 Dr. Muhammad Yasir
  • Master
2.01.368 Microrobotics Selected Topics Friday: 10:00 - 12:00, weekly (from 05/04/24)

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
2.01.5128 AI in Energy Systems Monday: 14:00 - 16:00, weekly (from 08/04/24)

Description:
Seminar 2 Jörg Bremer
  • 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
2.01.950 Exploring Research Data Management Wednesday: 08:00 - 10:00, weekly (from 08/04/24)
Thursday: 16:00 - 18:00, weekly (from 04/04/24)

Description:
In this course students will learn about different methods of research data management. Students are introduced to the topics of: - research data, - digital research objects, - data management plans, - data management services, - the FAIR criteria (Findable, Accessible, Interoperable and Reusable) for digital research object and how to fulfill them, - Open Science. They will learn about the importance of data management when working together as groups, as well as when working alone, and how to plan their data management for different research scenarios. After the course, the students will be able to handle different types of digital research objects in a reproducible and FAIR way. They will know about different digital research objects such as electronic lab notes, csv, research software etc. Goals of the course: Students will be able to identify data in its different forms. They will be able to identify different types of digital research objects that will be collected in a research project and analyze the project to come up with a fitting data management plan. They will be able to identify the data lifecycle and plan accordingly to ensure that data is preserved when needed. Furthermore, students will be familiarized with the term research data management, research data services and different tools to aid in research data management. Students learn about the FAIR criteria and how to create digital research objects which fulfill these criteria. In this course students will learn about different methods of research data management. Students are introduced to the topics of: - research data, - digital research objects, - data management plans, - data management services, - the FAIR criteria (Findable, Accessible, Interoperable and Reusable) for digital research object and how to fulfill them, - Open Science. They will learn about the importance of data management when working together as groups, as well as when working alone, and how to plan their data management for different research scenarios. After the course, the students will be able to handle different types of digital research objects in a reproducible and FAIR way. They will know about different digital research objects such as electronic lab notes, csv, research software etc. Goals of the course: Students will be able to identify data in its different forms. They will be able to identify different types of digital research objects that will be collected in a research project and analyze the project to come up with a fitting data management plan. They will be able to identify the data lifecycle and plan accordingly to ensure that data is preserved when needed. Furthermore, students will be familiarized with the term research data management, research data services and different tools to aid in research data management. Students learn about the FAIR criteria and how to create digital research objects which fulfill these criteria.
Lecture - Prof. Dr. Astrid Nieße
Stephan Alexander Ferenz, M. Sc.
Thomas Wolgast, M. Sc.
M. Sc. Alexandro Steinert
Graduate School OLTECH
  • Master
2.01.5454 Current Topics in Artificial Intelligence for Health Friday: 14:00 - 16:00, weekly (from 05/04/24)

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. The seminar will be held in a roleplaying format where students present on specific aspects of the paper under consideration which will then be discussed in the whole group in biweekly meetings. 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. The seminar will be held in a roleplaying format where students present on specific aspects of the paper under consideration which will then be discussed in the whole group in biweekly meetings.
Seminar 2 Prof. Dr. Nils Strodthoff
Juan Lopez Alcaraz
  • Master
2.01.586 Privacy-preserving Data-driven Optimization Thursday: 12:00 - 14:00, weekly (from 04/04/24)

Description:
Seminar 2 Prof. Dr. Sebastian Lehnhoff
Jörg Bremer
  • Master
2.01.801-D Forschungsseminar Applied Artificial Intelligence (Bachelor/Masterseminar) The course times are not decided yet.
Description:
Seminar - Michael Barz, M. Sc.
Prof. Dr. Daniel Sonntag
Ilira Troshani
  • Bachelor
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
Ilira Troshani
Hannes Kath
Prof. Dr. Daniel Sonntag
  • 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
2.01.5460 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 (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
Ilira Troshani
Hannes Kath
Prof. Dr. Daniel Sonntag
  • Master
18 Seminars

Top