Current and Past courses
New courses at the University of Stuttgart
- Foundation Models, University of Stuttgart, WS 2023/24 (Lecture with Exercise, 6 ECTS, 4 SWS), jointly with Steffen Staab and Matthias Niepert.
- Learning with Less: Resource- and Data-efficient Visual Recognition, University of Stuttgart, WS 2023/24 (Hauptseminar, 3 ECTS, 2 SWS).
- Automotive and Assistive Computer Vision, University of Stuttgart, SS 2024 (Lecture with Exercise, 6 ECTS, 4 SWS).
- Machine Perception and Learning, University of Stuttgart WS, 2023/24 (Lecture with Exercise, 6 ECTS, 4 SWS), jointly with Andreas Bulling.
- Foundation Models, University of Stuttgart, WS 2023/24 (Lecture with Exercise, 6 ECTS, 4 SWS), jointly with Steffen Staab and Matthias Niepert.
Past courses at KIT
- Deep Learning for Computer Vision I: Basics (at KIT)
- Deep Learning for Computer Vision II: Advanced Topics (at KIT)
- Practical Course Computer Vision for Human-Computer Interaction (at KIT)
- Through my Bachelor and Master studies, I have been a tutor in the practical course Fundamentals of Programming (three times) and the preparation course Mathematics for Computer Scientists.
- Mentoring: I am happy to support computer science students at TUM as a mentor in the scope of the TUM Mentoring Program.
Master and bachelor theses
If you are a student at the University of Stuttgart and are passionate about one of {machine learning, deep learning, computer vision} and want to apply what you have learned in the area of activity recognition / video comprehension in your thesis - please contact me with your subject starting with [Thesis-IntelliSensing], your a transcript of records and a few sentences about yourself.
Past supervised theses
- Jonas Steinhäuser, "Machine learning-based prediction of head injury severity in car crashes from car interior information", Master Thesis, (co-supervision, thesis conducted at Porsche), 06.2023.
- Bora Pilav, "Privacy-Preserving Driver Activity Recognition", Bachelor Thesis, 11.2022.
- Alperen Ayar, "Deep visual transformers for driver maneuver prediction", Bachelor Thesis, 10.2022.
- Ping-Cheng Wei, "Deep Learning-based Multi-modal Depression Estimation using Knowledge from Micro-facial Expressions", Bachelor Thesis, 04.2022.
- Calvin Tanama, "Data distillation for efficient action recognition with student-teacher networks", Bachelor Thesis, 05.2022.
- Zdravko Marinov, "Deep Learning-based Unsupervised Domain Adaptation for Activity Recognition from Synthetic Training Data", Master Thesis, 12.2021.
- Vincent Pfäfflin, "Curriculum Learning for Human Activity Recognition with Imbalanced Training Data", Bachelor Thesis, 08.2021.
- Simon Reiß, "Zero-Shot Recognition of Composite Activities in Context of Driver Observation", Master Thesis, 02.2020.
- Yilin Ji, "Machine Learning for Situation Analysis of Automated Vehicle using Small Data Sets", Master Thesis, 07.2019, (co-supervision, thesis conducted at BOSCH).
- Chaoxiang Ma, "Reliability of Deep Convolutional Neural Networks for Activity Recognition", Bachelor Thesis, 01.2019.
- Patrick Gebert, "Vehicle Maneuver Prediction with 3D Convolutional Neural Networks Based on Driver Observation", Master Thesis, 07.2018.
- Tim Pollert, "Fusion Methods for Multimodal Gesture Recognition with Convolutional Neural Networks", Master Thesis, 06.2018.