Alexander Immer

I am a PhD student at the Max Planck ETH Center for Learning Systems advised by Gunnar Rätsch (ETH Zürich) and Bernhard Schölkopf (MPI-IS Tübingen). I will spend my exchange year at MPI starting in February 2022.

My research focuses on probabilistic machine learning and data science. I am particularly interested in approximate Bayesian inference for neural networks. Currently, I am working on methods for incorporating prior knowledge, quantifying uncertainty, and selecting optimal neural networks from training data alone. I am further interested in applying such methods to biomedical data and relate them to causal inference.