Peter Auer received his PhD in mathematics from the Vienna University of Technology in 1992, working on probability theory with Pal Revesz and on Symbolic Computation with Alexander Leitsch. He then moved to Graz University of Technology, working on Machine Learning with Wolfgang Maass, and was appointed associate professor in 1997. He has also been research scholar at the University of California, Santa Cruz. In 2003 he accepted the position of full professor for Information Technology at the Montanuniversitaet Leoben. He has authored scientific publications in the areas of probability theory, symbolic computation, and machine learning, is a member of the editorial board of Machine Learning and Action Editor of the Journal of Machine Learning Research. He has been principal investigator on several research projects funded by the European Union. His current research interests include Machine Learning focused on autonomous learning and exploration algorithms, in particular multi-armed bandit problems and reinforcement learning.
- Algorithms and Uncertainty, Fall 2016. Visiting Scientist.