Güneş is a Departmental Lecturer in machine learning at the Department of Computer Science and a Senior Researcher in machine learning at the Department of Engineering Science, University of Oxford. He is also a Research Member of the Common Room at Kellogg College, a research consultant for Microsoft Research Cambridge, and a member of European Lab for Learning and Intelligent Systems (ELLIS).
He specializes in probabilistic programming and simulation-based inference, and applications at the intersection of machine learning and physical sciences. His other research interests include automatic differentiation, hyperparameter optimization, and evolutionary algorithms. He’s been working on enabling efficient probabilistic inference in large-scale simulators in particle physics, focusing on distributed training and inference at supercomputing scale. He is also involved in collaborations in heliophysics, cosmology, spacecraft collision avoidance, with collaborators at Lawrence Berkeley Lab, NYU, CERN, NASA, and ESA. He co-organizes the NeurIPS workshop ML4PhysicalSciences among other things.
OATML group members and collaborators are proud to be presenting 22 papers at NeurIPS 2020. Group members are also co-organising various events around NeurIPS, including workshops, the NeurIPS Meet-Up on Bayesian Deep Learning and socials. …Full post...
Muhammed Razzak, Panagiotis Tigas, Angelos Filos, Atılım Güneş Baydin, Andrew Jesson, Andreas Kirsch, Clare Lyle, Freddie Kalaitzis, Jan Brauner, Jishnu Mukhoti, Lewis Smith, Lisa Schut, Mizu Nishikawa-Toomey, Oscar Key, Binxin (Robin) Ru, Sebastian Farquhar, Sören Mindermann, Tim G. J. Rudner, Yarin Gal, 04 Dec 2020