Vice-Rector Christopher Lindinger presented Günter Klambauer with his venia legendi/habilitation certificate.
As a computer scientist at the JKU’s Institute for Machine Learning, Günter Klambauer’s post-doctoral dissertation describes ways in which Deep Learning and modern AI methods have revolutionized computer-aided drug development.
Those pursuing a habilitation/post-doc undergo an academic evaluation in regard to special qualifications that proves their ability to independently conduct academic/scientific research and teach the entire depth and breadth of their selected subject area [facultas docendi], This, in turn, is the prerequisite to grant authorization to teach that particular subject area [venia legendi].
About Günter Klambauer
After completing degrees in mathematics and biology at the University of Vienna, Klambauer came to the JKU in 2010 and embarked on research in the area of machine learning and bioinformatics, earning a PhD at the JKU in 2014. He was presented with the Austrian Life Science Award in 2012, and the Austrian Ministry of Science’s Award of Excellence in 2014 for using machine learning techniques in the areas of genetics and molecular biology. Recently, he has managed several data analysis groups as part of large projects together with several pharmaceutical companies. While Günter Klambauer's earlier research focused mainly on bioinformatics, his research focus shifted to Deep Learning and developing new machine learning methods. As part of an international scientific competition, the Tox21 Data Challenge, Günter Klambauer and his group won by developing the best method for predicting chemical toxicity.
Klambauer’s research currently focuses on developing general AI applications in life sciences. Klambauer currently holds a tenure-track professorship position for "AI in Drug Discovery", leads a research group "AI in Life Sciences" at the ELLIS unit Linz and at the LIT AI Lab, and conducts research at the JKU’s Institute for Machine Learning.