Past members

Maria Lomeli

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Manon Kok

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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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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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Alexandre Khae Wu Navarro

Alexandre is currently a PhD student supervised by Dr. Richard Turner and Dr. Carl Rasmussen. His main research interest lies in the intersection between Directional Statistics and probabilistic Machine Learning, both in fundamental and applied research. He is also interested in variational methods, causal inference, partially-observed Markov processes (encompassing change-point models). For an overview of [...]

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Yutian Chen

Yutian Chen joined the machine learning group as a research associate (Postdoc) in August 2013. He earned his B.E. of Electronic Engineering from Tsinghua University in China in June 2007 and Ph.D. of Computer Science from University of California, Irvine in the United States in June 2013. His research interests lie in the areas of [...]

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Maxim Rabinovich

Maxim Rabinovich received an AB (with Highest Honors) in Mathematics from Princeton in 2013. There, he worked with David Blei on context-sensitive topic modeling. At Cambridge, where he is supported by the Overseas Trust, he is a student of Zoubin Ghahramani. His primary research interests are in machine learning and natural language processing; he is [...]

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