Timo Heiß
About
I am a PhD student in the Machine Learning Interpretability subgroup under supervision of Giuseppe Casalicchio and Bernd Bischl since October 2025. My research interests center on making Machine Learning interpretable to increase trust and transparency, as well as on intersections of Interpretable Machine Learning with other areas of Machine Learning.
My current research focuses on feature effects, feature interactions, and functional decompositions. Previously, I have also worked on prompt optimization.
I obtained a Master's degree in "Statistics & Data Science" at LMU Munich and a Bachelor's degree in "Business Informatics - Data Science" at DHBW Ravensburg. Prior to my PhD studies, I gained five years of industry experience at Liebherr-Aerospace as a dual and working student, developing and deploying Machine Learning models with focus on interpretability.
Contact
Institut für Statistik
Ludwig-Maximilians-Universität München
Ludwigstraße 33
D-80539 München
Room 344, 3rd floor
timo.heiss [at] stat.uni-muenchen.de
Research Interests
- Interpretable Machine Learning
- Model-agnostic IML Methods
- Feature Effects, Interactions, and Functional Decompositions
- Intersections of IML
- (Prompt Optimization)