Dr Marc Deisenroth

Marc is PI of the SML group and Lecturer in the Department of Computing at Imperial College London. His research centers around data-efficient machine learning for robotics, control, time-series analysis, and signal processing.

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Dr Senanayak Sesh Kumar Karri

Sesh is a Leverhulme Centre for the Future of Intelligence research fellow for the Trust and Transparency project at the Statistical Machine Learning group, Imperial College, London. He has previously worked on structure learning of graphical models and submodular optimisation. He is now primarily interested in fairness, privacy and transfer learning etc.

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Hugh Salimbeni

Hugh’s research focuses on deep Bayesian models and approximate inference. Recently, he has been looking at deep Gaussian process models. These models are compositions of functions, much like deep neural networks, except rather than optimizing parameters we instead perform Bayesian inference. This is harder to do, but comes with many advantages, such as incorporation of prior knowledge, model uncertainty, and automatic regularization.

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Mr Sanket Kamthe

I did my undergraduate degree in Electronics and Telecommunications from University of Pune (2008), India, after which I worked in Telecom (2008-2010) and high energy physics (2011). I obtained my MSc in Information and Communication Engineering from TU Darmstadt, Germany (2013) and then worked as a Marie Curie research fellow in University of Twente, Netherlands before joining HiPEDs CDT program at Imperial.

For my PhD I am focusing on statistical machine learning methods for robotics and control. I am interested in using Gaussian Process based methods for non-parametric data modelling.

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