Humans, animals, and other living beings have a natural ability to autonomously learn throughout their lives and quickly adapt to their surroundings, but computers lack such abilities. Our goal is to bridge such gaps between the learning of living-beings and computers. We are machine learning researchers with an expertise in areas such as approximate inference, Bayesian statistics, continuous optimization, information geometry, etc. We work on a variety of learning problems, especially those involving supervised, continual, active, federated, online, and reinforcement learning. Please check out research and publications pages for a more exhaustive overview.
If you are interested in joining us, see the people page and the news below for current opportunities.
Tenured research scientist position available, see the official job posting.
Position for 3 year contract.
See here for details.
Invited talk by Emtiyaz Khan at Tübingen AI Center (Philipp Hennig’s group).
Invited talk by Emtiyaz Khan at Secondmind.
Invited talk by Emtiyaz Khan at Durham CDT Data Science Workshop.
Invited talk by Pierre Alquier at Ecology and Dependance 2021 (EcoDep) on [ Risk Bound for High Dimensional Time Series Completion ]