University of Cambridge, and Chief Scientist, Uber
Probability theory provides a mathematical framework for understanding learning and for building rational intelligent systems. I will review the foundations of the field of probabilistic AI. I will then highlight some current areas of research at the frontiers, touching on topics such as Bayesian deep learning, probabilistic programming, Bayesian optimisation, and AI for data science. I will also describe how we have organised research at Uber AI and where probabilistic machine learning fits in.
Zoubin Ghahramani FRS is Professor of Information Engineering at the University of Cambridge and Chief Scientist and VP of Artificial Intelligence at Uber Technologies Inc. He studied at the University of Pennsylvania, received his PhD from MIT, and was a postdoctoral fellow at the University of Toronto. He moved to the UK in 1998 as one of the founding faculty members of the Gatsby Computational Neuroscience Unit at UCL, and held a concurrent faculty appointment in the Machine Learning Department at Carnegie Mellon University for 10 years. He was the first Cambridge Director of the Alan Turing Institute, the UKís national institute for data science and AI and he co-founded Geometric Intelligence, an AI startup which was acquired by Uber and became the nucleus of Uberís AI organization. Zoubin is also currently Deputy Director of the Leverhulme Centre for the Future of Intelligence, studying the impact of AI on society, and a Fellow of St John's College, Cambridge. Zoubin is known for his pioneering work on probabilistic approaches to machine learning and artificial intelligence, and he has published over 300 research papers on these topics, as well as mentoring 76 PhD students and postdocs. In 2015, he was elected a Fellow of the Royal Society for his contributions to machine learning.