Team
Simon ReißSimon Reiß
Dr.-Ing. Simon Reiß
Young Investigator Group Leader
simon.reiss@kit.edu
https://simael.github.io/
Building 50.28; Room 116
Adenauerring 10
76131 Karlsruhe
Germany
Phone: +49 (0)721 608 44735
Bio
I am Simon Reiß a Young Investigator Research Group Leader at Karlsruhe Institute of Technology (KIT), Germany, leading the Sample-Efficient and Emergent Adaptative Lightweight Learning group.
I earned a Bachelor’s degree in Software Engineering from the University of Stuttgart and a Master’s degree in Computer Science at the Karlsruhe Institute of Technology (KIT) under the study profile artificial intelligence. In 2023, I earned a doctoral degree from KIT, where I conducted research in the Computer Vision for Human-Computer Interaction Lab on Semi-Weakly Supervised Learning for Label-efficient Semantic Segmentation in Expert-driven Domains with distinction, focusing on data-efficient learning paradigms for computer vision.
My research aims to advance innovative learning paradigms to develop efficient and robust computer vision models, particularly in low-data scenarios. I specialize in semi-weakly supervised learning and visual in-context learning, aiming to go beyond traditional supervision types and enable models to learn effectively from only few or imperfect annotations. My work is especially focused on scarce-resource imaging domains, where data efficiency and adaptability are critical to make use of vision systems.
Projects
KiKIT: The Helmholtz Pilot Program Core-Informatics at KIT
KiKIT is a project for research on novel generic methods the areas of algorithm- and software engineering, data analysis, and systems, where I contribute with my computer vision and machine learning research. The SEEALL Young Investigator Group is directly funded by KiKIT since April 2026.
HIDSS4HEALTH
In the Helmholtz Information & Data Science School for Health, I contribute to a project on rooting AI models in multi-modal medical guidelines.
Teaching
Deep Learning for Computer Vision II: Advanced Topics
I am the main organizer and lecturer of this collaborative lecture (3 ECTS), which is offered together with the Computer Vision for Human Computer Interaction group in each winter term; material is available here.
Seminars and Practical Courses
On a recurring basis, I also supervise seminars (Seminar Computer Vision for Human-Computer Interaction, Seminar on Multimodal Large Language Models) and occationally practical courses (Practical Course Computer Vision for Human-Computer Interaction).
Student Theses
I have been supervising more than 15 student theses. Please take a look at our current offers!
Publications
See the group publication page.