New CLS faculty members at ETH Zurich
cls 03 August 2020 News
Five researchers from four different departments at ETH Zurich join our body of CLS faculty members: Afonso Bandeira (D-MATH), Caroline Uhler (D-BSSE), Klaas Prüssmann and Fisher Yu (both D-ITET), and David Steurer (D-INFK). Welcome!
Afonso Bandeira was appointed Full Professor of Mathematics at the Department of Mathematics (D-MATH) in May 2019. He writes: “I am interested in the Mathematics of Data Science, broadly defined. This often involves probability, statistics, computer science, and optimization.” Klaas Prüssmann has been a Full Professor for Bioimaging at the Department for Information Technology and Electrical Engineering (D-ITET) since 2008. Klaas Prüssmann heads the Magnetic Resonance (MR) Technology and Methods Group at the Institute for Biomedical Engineering of ETH and University of Zurich. The MR Technology group is dedicated to advancing magnetic resonance for biomedical research and healthcare applications, combining expertise in physics, engineering and the life sciences. David Steurer was appointed Associate Professor of Theoretical Computer Science at the Department for Computer Science (D-INFK) in July 2020. David Steurer’s research investigates fundamental questions regarding efficient computation (complexity theory), with particular reference to optimisation and data analysis. Caroline Uhler was appointed Full Professor of Machine Learning, Statistics and Genomics at the Department for Biosystems Science and Engineering (D-BSSE) located in Basel, in July 2019. She writes: “My research focuses on statistics, machine learning and computational biology, in particular on graphical models, causal inference, algebraic statistics and applications to genomics.” Fisher Yu was appointed Tenure Track Assistant Professor of Computer Vision at the Department for Information Technology and Electrical Engineering (D-ITET) in July 2019. Fisher Yu conducts research on computer vision and machine learning. His work covers a wide spectrum, ranging from the basics of machine image and video analysis through to practical applications, such as in self-driving vehicles. His principal tools are neural networks, which he both applies and develops further.