Probabilistic Machine Learning and AI: Zoubin Ghahramani

AAAI-18 / IAAI-18 Joint Invited Speaker 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. Zoubin Ghahramani FRS is Professor of Information Engineering at the University of Cambridge and Chief Scientist at Uber. He is also Deputy Director of the Leverhulme Centre for the Future of Intelligence, and a Fellow of St John’s College. He was a founding Cambridge Director of the Alan Turing Institute, the UK’s national institute for data science. He has worked and studied at the University of Pennsylvania, MIT, the University of Toronto, the Gatsby Unit at University College London, and Carnegie Mellon University. His research focuses on probabilistic approaches to machine learning and artificial intelligence, and he has published over 250 research papers on these topics. He was co-founder of Geometric Intelligence (now Uber AI Labs) and advises a number of AI and machine learning companies. In 2015, he was elected a Fellow of the Royal Society for his contributions to machine learning.