After studying Mathematics and Biology at the University of Vienna, Günter Klambauer started his research in bioinformatics and
machine learning in 2010 at the Johannes Kepler University Linz, where he earned his PhD in 2014. His machine learning methods for
genetics were awarded with the Austrian Life Science Award 2012 and the Award of Excellence of the Austrian Ministry of Science
in 2014. In the past years, he has led several data analysis groups in large projects with pharma industry.
While Dr. Klambauer’s research has mainly been concerned with machine learning for molecular biology in earlier years,
his research focus is currently on Deep Learning and Drug Discovery, concretely building AIs for automated drug discovery.
This has led to the development of the best performing methods at the 2013 DREAM Toxicogenetics challenge and the win at the
Tox21 Data Challenge 2015. He has published several impactful papers, such as "Deeptox: toxicity prediction using Deep Learning"
introducing Deep Learning on molecules, and "Self-normalizing networks" crafting a novel type of neural networks.
Günter Klambauer is currently leading the "AI in Life Sciences" group of the LIT AI Lab at the Johannes Kepler University Linz.