Computational and Biological Learning Lab

Erik Daxberger


Erik is a PhD candidate supervised by Dr José Miguel Hernández-Lobato. As a Cambridge-Tübingen fellow, he is spending a year of his PhD at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, supervised by Bernhard Schölkopf. He is also collaborating with Emtiyaz Khan at the Approximate Bayesian Inference Team of the RIKEN Center for Advanced Intelligence Project in Tokyo, Japan. His research interests broadly revolve around machine learning and artificial intelligence, with a current focus on methods at the intersection of probabilistic modeling and deep learning.

Before embarking on his PhD, he obtained a Master’s degree in Computer Science from ETH Zurich, where he also did research on discrete and mixed-variable Bayesian optimization with Andreas Krause. Prior to that, he was based in his hometown of Munich, Germany, where he obtained a Bachelor’s degree in Computer Science from Ludwigs-Maximilians-Universität, and did a research internship at Siemens, working on statistical relational learning with Volker Tresp. He also spent a year at the National University of Singapore, where he did research on batch Bayesian optimization with Bryan Kian Hsiang Low.