Technical University of Munich: TUM’s ninth and tenth Humboldt Professorships

Stefanie Jegelka completed her doctoral studies at the University of Tübingen and ETH Zurich in 2012, after which she conducted postdoctoral research at the University of California, Berkeley. She was then appointed Associate Professor at MIT in Cambridge. As an information scientist she is an expert in artificial neural networks, which among other things can be used to make reliable predictions on the properties of certain molecules, combinations of medicinal active ingredients and their potential side-effects.

Mathematician Suvrit Sra received his PhD from the University of Texas at Austin in 2007 and until 2015 conducted research in Tübingen at the Max Planck Institute for Intelligent Systems. He is currently an Associate Professor at MIT. Suvrit Sra’s fundamental methodological work on a variety of optimization questions has contributed greatly to the enormous progress made in the field of machine learning over the past few years.

Stefanie Jegelka is to take on a position at the TUM Department of Informatics, while Suvrit Sra is to join the Department of Mathematics. Both professors shall be future members of the TUM School of Computation, Information and Technology, which his being formed from the TUM Informatics, Mathematics and Electrical and Computer Engineering departments as part of the TUM AGENDA 2030. The two shall help to establish an important link to the Munich Data Science Institute (MDSI), established in 2020 as part of the Excellence Strategy, as well as to the Munich Center for Machine Learning (MCML), which is supported by the German Federal Ministry of Education and Research. TUM is thus strategically strengthening its internationally leading core area of expertise in Machine Learning and Artificial Intelligence.

Comments are closed.