Session 1 | Invited talk: Michael Bronstein, "Geometric Deep Learning for Functional Protein Design"

I am a Departmental Lecturer (Assistant Professor) in Machine Learning at the Department of Computer Science and a Lecturer in Computer Science at Jesus College, University of Oxford, where I lead the Oxford AI for Science Lab. I work on probabilistic machine learning, with particular focus on generative modeling, probabilistic programming, deep learning, and simulation-based inference. Previously I was a postdoc with Frank Wood, working on probabilistic programming. Before Oxford, I was a postdoc with Barak Pearlmutter at the Brain and Computation Lab, National University of Ireland Maynooth, where I specialized in automatic differentiation in higher-order functional languages, and nesting of forward and reverse differentiation. I did my PhD at Universitat Autònoma de Barcelona, where my supervisor was Ramon Lopez de Mantaras at the Artificial Intelligence Research Institute (IIIA/CSIC), working on computational analogy, commonsense reasoning, and graph-based evolutionary algorithms. Before this, I received a MSc degree from Chalmers University of Technology, where I was working on artificial life and computational physics in the Complex Adaptive Systems program. I am also a member of the Torr Vision Group (TVG) at the Department of Engineering Science and the Oxford Applied and Theoretical Machine Learning Group (OATML). I am a Research Member of the Common Room at Kellogg College, and a member of the European Lab for Learning and Intelligent Systems (ELLIS) Oxford Unit. Previously I was a research consultant for Microsoft Research Cambridge. I am involved in NASA and ESA Frontier Development Lab programs as faculty and member of the AI Technical Committee.