Latest news

  • 9 papers with MLG authors to appear at ICLR 2020 and AISTATS 2020February 23, 2020, 1:37 pm

    6 papers with MLG authors will appear at ICLR 2020 in Addis Ababa, Ethiopia. Jonathan Gordon*, Wessel Bruinsma*, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard Turner Convolutional Conditional Neural Processes (oral) Paper Roman Novak, Lechao Xiao, Jiri Hron, Jaehoon Lee, Alexander A. Alemi, Jascha Sohl-Dickstein, Samuel S. Schoenholz Neural Tangents: Fast and Easy […]

  • 10 papers with MLG authors to appear at NeurIPS 2019September 19, 2019, 11:45 am

    10 papers with MLG authors will appear at NeurIPS 2019 in Vancouver, Canada. James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes (spotlight) Paper Wenbo Gong, Sebastian Tschiatschek, Richard E. Turner, Sebastian Nowozin, José Miguel Hernández-Lobato, Cheng Zhang Icebreaker: Efficient Information Acquisition with […]

  • Best Paper Award at ICML 2019September 19, 2019, 11:35 am

    Congratulations to our PhD student David R. Burt, Prof. Carl E. Rasmussen and our PhD alumnus Mark van der Wilk (now at for receiving a Best Paper Award at ICML 2019 in Long Beach, CA, USA, for their paper Rates of Convergence for Sparse Variational Gaussian Process Regression (Paper)!

  • 12 papers with MLG authors appeared at ICML 2019September 19, 2019, 11:27 am

    12 papers with MLG authors appeared at ICML 2019 in Long Beach, CA, USA. David R. Burt, Carl E. Rasmussen and Mark van der Wilk Rates of Convergence for Sparse Variational Gaussian Process Regression (Best Paper Award) Paper Francisco J. R. Ruiz and Michalis K. Titsias A Contrastive Divergence for Combining Variational Inference and MCMC […]

  • 13 papers with MLG authors to appear at ICML 2018May 23, 2018, 11:23 am

    13 papers with MLG authors will appear at ICML 2018 in Stockholm, Sweden. Matej Balog, Ilya Tolstikhin, and Bernhard Schölkopf Differentially Private Database Release via Kernel Mean Embeddings Niki Kilbertus, Adrià Gascón, Matt Kusner, Michael Veale, Krishna Gummadi and Adrian Weller Blind Justice: Fairness with Encrypted Sensitive Attributes. Jiri Hron, Alexander G. de G. Matthews […]

  • Seventeen Recent Papers from MLGFebruary 18, 2018, 9:47 am

    INTERNATIONAL CONFERENCE ON LEARNING REPRESENTATIONS, Vancouver. 2018 Yingzhen Li and Richard E. Turner. Gradient Estimators for Implicit Models. Alexander. G. de G. Matthews, Jiri Hron, Mark Rowland, Richard E. Turner, Zoubin Ghahramani. Gaussian Process Behaviour in Wide Deep Neural Networks. David Janz, J. van der Westhuizen , Brooks Paige, M. Kusner and José Miguel Hernández-Lobato […]

  • Dr Adrian Weller appointed as Programme Director for Artificial Intelligence at The Alan Turing InstituteFebruary 10, 2018, 10:02 am

    MLG member Adrian Weller has been appointed as the Programme Director for Artificial Intelligence at The Alan Turing Institute. More details can be found here.

  • Twelve papers with MLG authors to appear at NIPS 2017September 18, 2017, 12:21 pm

    “Convolutional Gaussian Processes.”, Mark van der Wilk, Carl Edward Rasmussen and James Hensman – CHOSEN FOR AN ORAL PRESENTATION. “Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs.”, Rowan McAllister and Carl Edward Rasmussen “Real Time Image Saliency for Black Box Classifiers.” Piotr Dabkowski, Yarin Gal “What Uncertainties Do We Need in Bayesian Deep Learning for Computer […]

  • Prize winning papers from MLG at ICML 2017August 10, 2017, 3:54 pm

    Several papers from MLG have won prizes at ICML 2017. Congratulations to everyone involved! Main Conference Track Best Paper Honourable Mention Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller Lost relatives of the Gumbel trick ICML Workshop on Human Interpretability in Machine Learning Best paper award Isabel Valera, Melanie Fernandez-Pradier, and Zoubin Ghahramani. General Latent […]

  • Two Postdoctoral Research Positions Available in the Machine Learning GroupAugust 10, 2017, 3:45 pm

    We are seeking two highly creative and motivated Research Assistants/Associates to join the Machine Learning Group at the University of Cambridge. The positions are for up to 24 months with a possible extension. Details below! (Closing Date: 7 September 2017) (Closing Date: 7 September 2017) The two positions are funded by Samsung. The […]

  • Ten papers with MLG authors to appear at ICML 2017June 1, 2017, 11:03 am

    Ten papers including authors from the Cambridge Machine Learning Group will appear at the International Conference for Machine Learning (ICML) 2017. They are: Li Y. and Gal Y. Dropout inference in Bayesian neural networks with alpha-divergences. Hernández-Lobato J. M., Requeima J., Pyzer-Knapp E. O. and Aspuru-Guzik A. Parallel and Distributed Thompson Sampling for Large-scale Accelerated […]

  • Alessandro Ialongo awarded Qualcomm Innovation FellowshipMay 12, 2017, 5:16 pm

    MLG graduate student Alessandro Ialongo has been selected for the 2017 Qualcomm Innovation Fellowship. He was awarded $40,000 for his innovation proposal titled “Learning and Decision-Making for Autonomous Behaviour”. The fellowship also involves the assignment of a Qualcomm researcher as mentor to facilitate close collaboration and interaction with Qualcomm Research & Development.

  • Three recent papers from MLGMay 11, 2017, 3:56 pm

    We wish to highlight three recent papers led by members from the group. The text can be found on the authors’ personal pages. Mark Rowland, Aldo Pacchiano and Adrian Weller. Conditions beyond treewidth for tightness of higher-order LP relaxations International Conference on Artificial Intelligence and Statistics (AISTATS) 2017 Alexander G. de G. Matthews, Mark van […]

  • Adrian Weller elected as David MacKay Newton Research FellowMarch 27, 2017, 9:09 am

    Prof Sir David MacKay was an amazing man, who until recently was part of our group. David was a terrific researcher and teacher in machine learning, and a passionate campaigner for social good through his work on energy. He passed away tragically last year. David was a fellow at Darwin College. With help from the […]

  • Postdoc position to study Trust and Transparency aspects of Artificial IntelligenceNovember 29, 2016, 2:45 pm

    The Leverhulme Centre for the Future of Intelligence (CFI; and the Machine Learning Group ( ) at the University of Cambridge invite applications for a Postdoctoral Research Associate in the study of trust and transparency in Artificial Intelligence (AI). The appointment will be for 3 years. CFI is a new, highly interdisciplinary research centre […]

Machine Learning Group @ The University of Cambridge

Group Members


Senior Researchers



Adam Scibior (postdoc at the University of British Columbia)
Akisato Kimura (group leader at NTT Communication Science Laboratories)
Gintare Karolina Dziugaite (Fundamental Research Scientist at Element AI)
Mateo Rojas-Carulla (software engineering at Google)
Paul Rubenstein (Machine Learning Research Engineer at Apple in Zurich)
Matej Balog (research scientist at DeepMind)
Matthias Bauer (research scientist at DeepMind)
Robert Peharz (Assistant Professor at Eindhoven University of Technology)
Francisco Jesus Rodriguez Ruiz (research scientist at DeepMind)
Kristoffer Stensbo-Smidt (postdoc at Technical University of Denmark)
Yichuan Zhang (director at Boltzbit Limited)
Eric Nalisnick (assistant professor at University of Amsterdam)
Niki Kilbertus (group leader at HelmholtzAI in Munich)
Cuong V. Nguyen (Applied Scientist, Amazon)
Mark Rowland (Research Scientist, DeepMind)
Alexander G. de G. Matthews (Research Scientist, DeepMind)
Manon Kok (Assistant Professor, Delft University of Technology)
Shixiang (Shane) Gu (Research Scientist, Google Brain)
Yingzhen Li (Research Scientist, Microsoft Research)
Amar Shah (CEO and Founder, Wayve)
Maria Lomeli Garcia (Research Scientist, Babylon Health)
Thang Bui (Lecturer, University of Sydney)
Mateo Rojas-Carulla (Research Scientist, Facebook AI Research)
Alexandre Navarro (Senior Data Scientist, AstraZeneca)
Mark van der Wilk (Senior Machine Learning Researcher,
Rowan McAllister (Post-Doc, University of California Berkeley)
Isabel Valera (Group Leader, Max Planck Institute for Intelligent Systems)
Sébastien Bratières
Yarin Gal (Associate Professor, University of Oxford)
Jan-Peter Calliess (Senior Research Fellow, University of Oxford)
Jes Frellsen (Associate Professor, IT University of Copenhagen)
David Lopez-Paz (Research Scientist, Facebook AI Research)
Matthew W. Hoffman (Research Scientist, Google DeepMind)
Creighton Heaukulani (Goldman Sachs)
Sara Wade (Assistant Professor, University of Warwick)
Yutian Chen (Research Scientist, Google DeepMind)
Felipe Tobar (Research Fellow, University of Chile)
Alex Davies (Software Engineer, Google)
Roger Frigola (Engineering Consultant)
James R. Lloyd (Head of Data Science, Qlearsite)
Maxim Rabinovich (PhD Student, UC Berkeley)
Konstantina Palla (Research Scientist, Microsoft Research Cambridge)
Neil M. T. Houlsby (Google Research, Zurich)
Daniel M. Roy (Assistant Professor, University of Toronto)
Jose Miguel Hernandez-Lobato (Post-Doc, Harvard, now Lecturer, Cambridge)
David Duvenaud (Assistant Professor, University of Toronto)
Andrew G. Wilson (Assistant Professor, Cornell University)
Novi Quadrianto (Assistant Professor, University of Sussex)
David Knowles (Post-Doc, Stanford University)
Peter Orbanz (Assistant Professor, Columbia University)
Joaquin Quiñonero Candela (Director of Engineering, Facebook)
Jurgen Van Gael (Data Science Director, Rangespan, bought by Google, now at Facebook)
Ryan P. Adams (Assistant Professor, Harvard University, also at Twitter Cortex)
Karsten Borgwardt (Professor, ETH Zurich)
John P. Cunningham (Assistant Professor, Columbia University)
Marc Deisenroth (Lecturer, Imperial College London)
Ferenc Huszar (Magic Pony, now Machine Learning Research Lead, Twitter Cortex Vx)
Finale Doshi-Velez (Assistant Professor, Harvard University)
Katherine Heller (Assistant Professor, Duke University)
Simon Lacoste-Julien (Researcher, INRIA/Ecole Normale Superior)
Iain Murray (Reader, University of Edinburgh)
Shakir Mohamed (DeepMind, bought by Google) 
Pedro Ortega (Postdoc, University of Pennsylvania)
Fernando Perez-Cruz (Associate Professor, University Carlos III, Madrid, also at Bell Labs)
Ricardo Silva (Lecturer, University College London)
Ed Snelson (Microsoft Research, now Head of Applied Research,
Fernando de la Torre (Associate Professor, Carnegie Mellon University)
Sinead Williamson (Assistant Professor, UT Austin)
Ryan Turner (Northrop Grumman)

Taught Courses

4F13: Machine Learning

Taught by Zoubin Ghahramani and Carl Rasmussen. Course web page.

Previous events

The 2009 Machine Learning Summer School was held in Cambridge on August 29th – September 10th.
Machine Learning Reading Group @ CUED
Machine Learning Seminar Group
Advanced Tutorial Lecture Series on Machine Learning
Non-Parametric Bayes Tutorial Course (October 9, 16 and 28, 2008)

Bayesian statistics in other labs

Machine Learning and Perception Group @ Microsoft Research Cambridge

Chris Bishop | Tom Minka

Statistical Laboratory

Phil Dawid | Richard Samworth | David Spiegelhalter

Computer Lab

Sean Holden

Signal Processing and Communications @ CUED

Simon Godsill | Sumeetpal Singh