Past members

Maria Lomeli

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Manon Kok

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Cuong V Nguyen

Please visit Cuong Nguyen’s homepage at: https://sites.google.com/site/nvcuong92/

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Kai Xu

Kai graduated from Homerton College, University of Cambridge with M.Phil in Machine Learning, Speech and Language Technology in 2016. He joined the group in 2016 as a research assistant, working on the probabilistic programming project Turing.jl with Prof. Zoubin Ghahramani and Dr. Hong Ge. Since September 2017, Kai is based at School of Informatics, University […]

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Jan-Peter Calliess

Mini Bio   NEWS: Starting May 2017,  I will join the Oxford-Man Institute and the Department of Engineering Science at Oxford as a Senior Research Fellow. From November 2014-April 2017 I was a research associate at the Engineering Department at the University of Cambridge. Predominantly working at the intersection of machine learning and control, I am […]

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Mark Rowland

I’m a Research Scientist at DeepMind. I’m interested in many areas across machine learning, statistics, probability, and optimisation, and interactions with areas of pure maths such as group theory and optimal transport theory. To date, I’ve worked on areas including inference problems for discrete graphical models, Monte Carlo methods (particularly over non-Abelian groups), reinforcement learning, […]

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Nilesh Tripuraneni

Nilesh Tripuraneni graduated from Harvard with a B.A. in Physics. Before joining the Machine Learning Group at Cambridge, he worked at machine learning start-ups in Boston on problems in natural language processing and probabilistic programming. At Cambridge, he is funded by an overseas studentship from Trinity College. He is particularly interested in approximate inference, and […]

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Felipe Tobar

Felipe A. Tobar received the B.Sc. (2008) and M.Sc. (2010) degrees in Electrical and Electronic Engineering from Universidad de Chile and the Ph.D. in Signal Processing at Imperial College London (2014). Felipe is currently a Research Associate at CBL working with Dr Richard E. Turner and his research interests lie within the interface between signal processing […]

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Shane Gu

Shixiang (Shane) Gu received a B.ASc. in Engineering Science from the University of Toronto, where he did his undergraduate thesis with Professor Geoffrey Hinton on distributed training of neural networks. He then worked in Silicon Valley prior to joining the lab. He is jointly funded by the Cambridge-Tübingen PhD Fellowship, NSERC, and Google Focused Research […]

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Amar Shah

Please click here for my personal page. Amar Shah joined the group in 2012 after working as a Quantitative Strategist at Goldman Sachs. Before this he obtained a BA and an MMath in Mathematics, also from Cambridge University. His research interests lie in Bayesian nonparametrics, in particular he studies the beta and Bernoulli processes and […]

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Matthew W. Hoffman

Matt received his Ph.D. in Computer Science from the University of British Columbia in 2013 following a B.Sc. in CS and Math from the University of Washington. He joined the group as a Research Associate (postdoc) in July of 2013. His research interests focus on probabilistic methods of decision making both in terms of long-term […]

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Daniel Hernández Lobato

My research interests are in the field of machine learning with an emphasis in linear Bayesian approaches that incorporate the assumption of sparsity. Since November 2009 to September 2011 I worked as postdoc researcher in the Machine Learning Group of the ICTEAM of the Université catholique de Louvain. Specifically, in the research project “Rheumagene”. This project tries to obtain […]

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