Professor Marc Deisenroth is the DeepMind Chair in Artificial Intelligence at University College London and PI of the Statistical Machine Learning Group at UCL. He also holds a visiting faculty position at the University of Johannesburg. From 2014 to 2019, Marc was a faculty member in the Department of Computing, Imperial College London. Marc’s research interests center around data-efficient machine learning, probabilistic modeling and autonomous decision making.
Marc was Program Chair of EWRL 2012, Workshops Chair of RSS 2013, and EXPO-Co-Chair at ICML 2020. He received Best Paper Awards at ICRA 2014 and ICCAS 2016. In 2019, Marc co-organized the Machine Learning Summer School in London with Arthur Gretton.
In 2018, Marc has been awarded The President’s Award for Outstanding Early Career Researcher at Imperial College. He is a recipient of a Google Faculty Research Award and a Microsoft PhD Grant.
In 2018, Marc spent four months at the African Institute for Mathematical Sciences (Rwanda), where he taught a course on Foundations of Machine Learning as part of the African Masters in Machine Intelligence. He is co-author of the book Mathematics for Machine Learning, published by Cambridge University Press.
Machine Learning: Data-efficient machine learning, Gaussian processes, reinforcement learning, Bayesian optimization, approximate inference, deep probabilistic models
Robotics and Control: Robot learning, legged locomotion, planning under uncertainty, imitation learning, adaptive control, robust control, learning control, optimal control
Signal Processing: Nonlinear state estimation, Kalman filtering, time-series modeling, dynamical systems, system identification, stochastic information processing