Courses Offered Academic Year 2023/24 - Summer

ChatGPT and Large Language Models in Education
This seminar covers current and varying topics from research and application in the field of generative AI in education. Based on the recent success of chatGPT and other large language models, it takes a look into the various fields of applying those models in the educational context. How can teachers and student exploit the advantages, what are the limits and the potential risks?
 Students will read and reflect upon current research in the area of generative AI in education. They can present current research results to other students and researchers as well as lead research discussions. They can summarize and evaluate the results of a paper in the form of a written research report.

TUM Online

Extended Reality for AI: Crafting Context-Aware Environments
This seminar discusses innovative methods for multimodal data collection and analysis techniques, focusing on Extended Reality (XR) environments. Specifically:
- Definition and importance of context-aware applications in XR environments.
- Classifying sources of context that can influence XR experiences.
- Methodologies and metrics for evaluating user experiences in context-aware XR applications.
- Design and technical implementation of context-aware XR systems.
- Multimodal data collection and evaluation of user studies.
- Identifying current frontiers of context-aware XR applications and future research opportunities.
- Final discussion and derivation of design principles for context-aware XR applications.

TUM Online
 

Large Language Models in Extended Realities
Recent developments in large language models open up unique opportunities for enhanced and personalized user experiences in virtual (VR) and augmented reality (AR). This hands-on course provides practical experience and training on large language models, with a particular focus on their integration and applications in VR and AR. The course introduces students to the fundamentals of large language models, including their architecture, training process, and performance evaluation. Through hands-on exercises, students will learn how large language models can be used in AR and VR applications such as speech recognition, language translation, and chatbots. They will also explore the ethical and social implications of using large-scale language models in augmented worlds, including concerns about bias, privacy, and human interaction. By the end of the course, students will have developed practical skills in using large language models in AR and VR, gained insight into their ethical and social implications, and be able to analyze their performance and limitations in practical applications.

TUM Online

Gaze-based Human-Computer Interaction
The block course at the end of the semester deals with the following topics:
- In-depth topics in the area of ​​visual perception (fixations, saccades, gaze patterns)
- Mechanisms of visual attention
- Measuring eye movements (eye tracking)
- Analysis of eye tracking data using machine learning methods
- Gaze-based control of computer systems
- Use of gaze information for interactive systems (including applications in virtual reality (VR) and augmented reality (AR))

 TUMOnline 

Human-AI Interaction
 The use of AI has significantly enhanced research and practical applications in numerous domains, resulting in the widespread integration of AI systems into our daily lives, such as recommendation systems, intelligent online search engines, decision support systems, and many more. However, the design and development of AI-based technology necessitate a meticulous and comprehensive examination of user experience and human factors, which are fundamental to ensuring the adoption and practical use of such systems.
  The purpose of this course is to delve into the intersection of AI systems and humans, critically analyzing different paradigms and methods for designing interactive, human-in-the-loop systems that facilitate a harmonious human-AI relationship. Additionally, this course will introduce methodological and human factors that are vital to ensuring interpretability, transparency, and trust in AI-based systems. In summary, this course serves as a bridge between Human-Computer Interaction and AI, providing a comprehensive understanding of the critical role of human factors in designing and developing practical AI systems that are user-friendly and meet the needs of diverse populations.

TUMOnline  

Practical Course (10 ECTS): Serious Games in Extended Reality (IN0012, IN2106)
 In this practical course, we will develop immersive serious games in the field of human-computer interaction. The main purpose is to gain practical experience with extended reality application development for different purposes such as learning new skills or training them, evaluating such applications, getting familiar with different sensors such as eye tracking for interaction purposes. The overall plan includes:
- Introduction to serious games
- Introduction to game engines and hands-on exercises
- Immersive game and application development beyond just entertainment purposes
- Interaction techniques such as eye and hand tracking

TUMOnline

Seminar (5 ECTS): Recent Advances in Privacy (IN0014, IN2107)
- Usable privacy and security
- Differential privacy
- Information privacy, tech policy
- Privacy enhancing technologies
- Privacy-preserving machine learning

 The sessions will be devoted especially to develop theoretical understanding of specific privacy topics such as usable privacy and security, differential privacy, information privacy, various privacy enhancing technologies, and privacy-preserving machine learning. In the beginning of the semester, a general introduction to the aforementioned topics will be done. Then, each student will pick a topic by selecting 1-2 research papers provided by the lecturers and study those over the semester with the help of experienced lecturers and tutors.
  In addition, in each session, presentations on the selected topics will be carried out by the students. Apart from presentations, the students are also supposed to provide their written report on their selected topic. Regular communication with experienced tutors will ensure in-depth understanding of the selected topic by the students.

TUMOnline 

Oberseminar "Human-Centered Technologies for Learning"
 In this course we will discuss state-of-the art methods and research ideas in Artificial Intelligence and Machine Learning and look at current trends of emerging multimedia technologies for learning.

TUMOnline

Courses Offered Academic Year 2023/24 - Winter

Gaze-based Human-Computer Interaction
The block course at the end of the semester deals with the following topics:

- In-depth topics in the area of ​​visual perception (fixations, saccades, gaze patterns)
- Mechanisms of visual attention
- Measuring eye movements (eye tracking)
- Analysis of eye tracking data using machine learning methods
- Gaze-based control of computer systems
- Use of gaze information for interactive systems (including applications in virtual reality (VR) and augmented reality (AR))

 TUMOnline  Moodle.

Human-AI Interaction
 The use of AI has significantly enhanced research and practical applications in numerous domains, resulting in the widespread integration of AI systems into our daily lives, such as recommendation systems, intelligent online search engines, decision support systems, and many more. However, the design and development of AI-based technology necessitate a meticulous and comprehensive examination of user experience and human factors, which are fundamental to ensuring the adoption and practical use of such systems.

  The purpose of this course is to delve into the intersection of AI systems and humans, critically analyzing different paradigms and methods for designing interactive, human-in-the-loop systems that facilitate a harmonious human-AI relationship. Additionally, this course will introduce methodological and human factors that are vital to ensuring interpretability, transparency, and trust in AI-based systems. In summary, this course serves as a bridge between Human-Computer Interaction and AI, providing a comprehensive understanding of the critical role of human factors in designing and developing practical AI systems that are user-friendly and meet the needs of diverse populations.

TUMOnline  Moodle.

Practical Course (10 ECTS): Serious Games in Extended Reality (IN0012, IN2106)
 In this practical course, we will develop immersive serious games in the field of human-computer interaction. The main purpose is to gain practical experience with extended reality application development for different purposes such as learning new skills or training them, evaluating such applications, getting familiar with different sensors such as eye tracking for interaction purposes. The overall plan includes:

- Introduction to serious games
- Introduction to game engines and hands-on exercises
- Immersive game and application development beyond just entertainment purposes
- Interaction techniques such as eye and hand tracking

TUMOnline  Moodle

Seminar (5 ECTS): Recent Advances in Privacy (IN0014, IN2107)
- Usable privacy and security
- Differential privacy
- Information privacy, tech policy
- Privacy enhancing technologies
- Privacy-preserving machine learning

 The sessions will be devoted especially to develop theoretical understanding of specific privacy topics such as usable privacy and security, differential privacy, information privacy, various privacy enhancing technologies, and privacy-preserving machine learning. In the beginning of the semester, a general introduction to the aforementioned topics will be done. Then, each student will pick a topic by selecting 1-2 research papers provided by the lecturers and study those over the semester with the help of experienced lecturers and tutors.

  In addition, in each session, presentations on the selected topics will be carried out by the students. Apart from presentations, the students are also supposed to provide their written report on their selected topic. Regular communication with experienced tutors will ensure in-depth understanding of the selected topic by the students.

TUMOnline Moodle

Oberseminar "Human-Centered Technologies for Learning"
 In this course we will discuss state-of-the art methods and research ideas in Artificial Intelligence and Machine Learning and look at current trends of emerging multimedia technologies for learning.

TUMOnline

Introduction to Python 
 In today's research landscape, Python has emerged as an indispensable tool for researchers across various disciplines. Its simplicity, versatility, and powerful libraries make it a preferred choice for data analysis, scientific computing, and research automation. Throughout this course, we will explore the fundamental concepts of programming using Python as our primary language. You will learn to write clean, efficient, and reproducible code, enabling you to perform complex data analysis tasks, visualize research findings, and automate repetitive research processes. Our hands-on approach ensures that you gain practical experience and apply Python programming techniques directly to your research domain. From working with data structures to implementing algorithms, you will develop the skills necessary to tackle research challenges with confidence. Moreover, we will delve into advanced Python libraries such as NumPy, Pandas, and Matplotlib, which are widely used in data analysis, machine learning, and visualization. You will discover how to leverage these tools to extract insights from complex datasets, analyze trends, and communicate your research findings effectively.

  As a researcher, you understand the significance of reproducibility and the importance of transparent methodologies. This course will equip you with best practices for documenting code, version control, and collaborating with colleagues, enabling you to maintain rigorous research standards throughout your projects.

TUMOnline

Mathematical Reasoning Using Large Language Models
 In recent years, large language models (LLMs) have proven to be powerful tools in natural language processing, yet their potential for mathematical problem-solving remains relatively untapped. This course aims to introduce students to the effective utilization of LLMs for mathematical reasoning tasks and explore potential directions for further improvement. By understanding how to harness the capabilities of LLMs and proposing innovative approaches, students can unlock new possibilities across diverse fields, such as scientific research, engineering, data analysis, and artificial intelligence. Through critical discussions and hands-on projects, students will develop the skills needed to leverage LLMs' full potential and advance the frontier of mathematical reasoning applications.

TUMOnline