Profile

After having received his B.Sc. in Business and Economics in 2020, Michael Gröger continued his studies in M.Sc. Data Science in Business and Economics at the University of Tuebingen. Currently, he is in his final year and writing his thesis on predictive domain adaptation at our group. During his studies, he gained professional experience involving machine learning at two start-ups and Bosch. When he's not coding you can probably find him playing water polo at the local swimming club.

His primary research interests revolve around domain adaptation and noisy data scenarios as you can find in semi- and weakly-supervised learning.

Publications

• "BoxShrink: From Bounding Boxes to Segmentation Masks", Michael Gröger*, Vadim Borisov*, Gjergji Kasneci, MILLanD Workshop at Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2022