Summary
Sach Mukherjee is Research Professor and co-lead of the Biostatistical Machine Learning theme at the BSU, Head of Statistics and Machine Learning at the DZNE in Bonn, Germany and Professor of Statistics and Machine Learning at the University of Bonn.
He earned a DPhil in machine learning at Oxford and has previously held faculty positions in Warwick and Amsterdam. His research interests centre on AI, ML and high-dimensional statistical methods, with a particular focus on causality, heterogeneous data and latent processes. He has been a Fulbright Fellow and a recipient of the Wolfson Research Merit Award of the Royal Society.
Selected Publications
- K. Lagemann, C. Lagemann & S. Mukherjee. “Invariance-based Learning of Latent Dynamics”. International Conference on Learning Representations (ICLR), 2024
- K. Lagemann, C. Lagemann, B. Taschler & S. Mukherjee. “Deep learning of causal structures in high dimensions under data limitations”. Nature Machine Intelligence, 5:1306–1316, 2023 (cover article)
- K. Perrakis, T. Lartigue, F. Dondelinger & S. Mukherjee. “Regularized Joint Mixture Models”. Journal of Machine Learning Research, 24(19):1-47, 2023
- M. F. Eigenmann, S. Mukherjee and M. H. Maathuis. “Evaluation of Causal Structure Learning Algorithms via Risk Estimation”. Uncertainty in Artificial Intelligence (UAI), 2020.
- F. Dondelinger and S. Mukherjee. “The joint lasso: high-dimensional regression for group structured data”. Biostatistics, 21(2):219-235, 2020
- S. M. Hill, C. J. Oates, D. Blythe and S. Mukherjee. “Causal Learning via Manifold Regularization”. Journal of Machine Learning Research, 20(127):1-32, 2019
