Team

Current group

Post-doctoral fellows

• Toshinori Kitamura. 2025/09/01–

PhD Students

• Roshan Shariff. 2015/12/29–

• Gábor Mihucz 2022/06/08–

• Vlad Tkachuk. Co-supervised with Xiaoqi Tan 2023/03/13–

• Siting Wang 2023/08/26–

• Shuai Liu. Co-supervised with Xiaoqi Tan 2024/08/07–.

Visiting students

• Daniel Kornai. 2026/09/15–2026/11/18; returning for two months beginning March 2027.

• Arya Akhavan, University of Oxford. March–May 2026.

• Davide Maran, Politecnico di Milano. 2024/09/18–2024/12/17.

• Jack Mayo, University of Amsterdam. 2023/10/04–early to mid-December 2023.

• Gaurav Mahajan, 2022 Summer & Fall

• Ayoush Sekhari, 2021 Summer & Fall

• Matt Regehr, 2021 Summer

• Philip Amortila, 2020 Summer, 2021 Summer

• Nivasini Ananthakrishnan, 2020 Summer

Alumni

Post-doctoral fellows, research associates

• Flore Sentenac. 2023/09/01-2024/04/01. Present position: Assistant Professor in the Department of Information Systems and Operations Management at HEC Paris.

• Zixin Zhong. Start: 2022 July End 2024 July. Present position: Assistant professor at the Data Science and Analytics Thrust (DSA) at the Hong Kong University of Science and Technology (Guangzhou).

• David Janz. Start: 2021 October (remotely, as a research associate for various administrative reasons, PDF start 2022 July) End 2024 August. Present position: Florence Nightingale Bicentenary Fellow in Statistics at the University of Oxford.

• Johannes Kirschner. 2021/09/01-2023/06/01. Present position: Senior Data Scientist at the Swiss Data Science Center (SDSC)

• Tadashi Kozuno. 02/2021-07/2022. Present position: Independent researcher.

• Sharan Vaswani. 11/2020-12/2021. Present position: Assistant Professor, Simon Fraser University

• Omar Rivasplata. Start: 2016 September with the PhD program, but already had a PhD in probability theory. At UCL from 2017 November, co-supervised with John-Shawe Taylor Present position: Associate Professor (Senior Lecturer) in Machine Learning at the University of Manchester.

• Omid Namaki Shoushtari 2015-2017. Last known affiliation: Amii.

• Chandrashekar Lakshmi Narayanan, 07/2016-07/2017. Present position: Assistant Professor in Computer Science and Engineering at IIT Madras.

• Karim T. Abou-Moustafa 07/2016-07/2017. Present position: Staff AI Applied Research Scientist at Intel R&D.

• Tor Lattimore 2014-2016. Present position: Research Scientist at Google DeepMind, London, working on provenance.

• András György. Present position: Senior Staff Research Scientist at Google DeepMind, London, UK.

• András Antos. Present position: Researcher in the Artificial Intelligence Research Group at the Budapest University of Technology and Economics.

• Dávid Pál 07/2009-07/2011. Present position: Staff Machine Learning Engineer at Uber.

• István Szita 2010-08/2011. Present position: Software engineer at Google, Zürich

• Barnabás Póczos 2007-2010. Present position: Associate Professor in the Machine Learning Department at Carnegie Mellon University.

• Sandra Zilles 06/2007-06/2009. Present position: Professor and Canada Research Chair in Computational Learning Theory at the University of Regina.

• Levente Kocsis 2005-2006. Present position: Senior researcher at HUN-REN SZTAKI, Hungary.

PhD students

• Alex Ayoub. Co-supervised with Dale Schuurmans. 2021/09/01–2026/08/31. Present position: Research Scientist at Google DeepMind.

• Gellért Weisz. UCL supervisor: Ilija Bugonovic. 2020/09/01-2024/02/05. Thesis: The Complexity of Reinforcement Learning with Linear Function Approximation Present position: Researcher at Google DeepMind, London.

• Mohammad Mahdi Ajallooeian 2013-2018, co-supervised with Martin Müller. Present position: Instructor at NorQuest College.

• Pooria Joulani 2012 September 1- 2018 December 11, co-supervised with András György.
  Thesis: Online optimization for machine learning: parallelism, adaptivity, and model selection. Present position: research scientist at DeepMind, London.

• Ruitong Huang 2011 February 9- 2017 September 28, co-supervised with Dale Schuurmans.
  Thesis: Instance-dependent analysis of learning algorithms.
  Present affiliation: XTX Markets, London.

• Özlem Aslan 2011 February 4-2017 January 5, co-supervised with Dale Schuurmans.
  Thesis: Convex Latent Modeling
  Formerly a Research Scientist at Google DeepMind, London, UK.

• Bernardo Avila Pires 2011 April 2-2016 October 19.
  Thesis: Toward Practical Reinforcement Learning Algorithms: Classification Based Policy Iteration and Model-Based Learning.
  Present position: research scientist at Deepmind, London, UK.

• Gábor Balázs 2009 November 20-2016 August 12, co-supervised with Dale Schuurmans.
  Thesis: Convex Regression: Theory, Practice, and Applications.
  Present position: Freelance Machine Learning Consultant and Researcher at G&G, Cartagena, Spain.

• Kiarash Shaloudegi ECE Student, , 2014 January 1-2016 March, co-supervised with András György and Wilsun Xu.
  Present position: Applied Scientist at Amazon.

• Hengshuai Yao 2008-2015.
  Thesis: Model-based Reinforcement Learning with State and Action Abstractions
  Formerly Principal Researcher at Huawei Noah's Ark Lab and HiSilicon.

• Yaoliang Yu 05/2009-11/2013, co-supervised with Dale Schuurmans.
  Thesis: Fast Gradient Algorithms for Structured Sparsity. Winner of the Outstanding PhD Thesis Award, Dept. of CS, U. of A and of the 2015 Best Doctoral Dissertation Award of the Canadian Artificial Intelligence Association. Present position: Associate Professor at the University of Waterloo and faculty member at the Vector Institute.

• Gergely Neu (BME) 2008-2013, co-supervised with Laci Györfi and András György.
  Thesis: Online Learning in Non-Stationary Markov Decision Processes. Winner of the Pro Scientia Gold Medal of the Hungarian Academy of Sciences, PhD student of the year at MTA SZTAKI for three years, MTA SZTAKI Young Researcher Award for excellent research activity. Present position: ICREA Research Professor in the Department of Economics and Business at Universitat Pompeu Fabra.

• Alireza Farhangfar. 2010 November 23-2013 March 15, co-supervised with Russ Greiner.
  Thesis: Novel Machine Learning Algorithms
  Present position: Data Scientist at Apple.

• Arash Afkanpour. 2010 March 18-2013 March 15, co-supervised with Michael Bowling.
  Thesis: Multiple Kernel Learning with Many Kernels
  Present position: Applied Machine Learning Scientist at the Vector Institute.

• Yasin Abbasi-Yadkori. 2009 March 4-2012 September 28.
  Thesis: Online Learning for Linearly Parametrized Control Problems
  Nominated for Outstanding PhD Thesis Award, Dept. of CS, U. of A.
  Present position: Staff Research Scientist and Tech Lead at Sapient Intelligence.

• Gábor Bartók. 2008 February 13-2012 July 8.
  Thesis: The role of information in online learning
  Winner of the 2013 Best Doctoral Dissertation Award Canadian Artificial Intelligence Association.
  Present position: Software Engineer at Google DeepMind, Zürich.

• Amir massoud Farahmand. 2006-2011. co-supervised with Martin Jagersand.
  Thesis: Regularities in Sequential Decision-Making Problems
  Winner of the Outstanding PhD Thesis Award, Dept. of Comp.Sci., U.of.A.
  Present position: Associate Professor at Polytechnique Montréal, core academic member at Mila, and Associate Professor (status-only) at the University of Toronto.

• Péter Torma (ELTE)
  Thesis: Towards efficient vision-based object tracking algorithms: rehabilitating visual information in particle filtering.
  Winner of the Pro Scientia Gold Medal of the Hungarian National Academy of Sciences.
  Present affiliation: Aconic.

• Zoltán Szamonek ELTE, 2007. Zoltan decided to quit his program and since then he is an SE at Google in Zürich.

MSc Students

• Thang Duc Chu. 2024/03/19–2026. Thesis: Lower Bound on Policy Gradient with Decreasing Stepsizes

• Samuel Robertson. 2023/04/17–2025/11/28 Thesis: Exploiting smoothness properties in stochastic control problems with uncontrolled volatility

• Alireza Bakhtiari. 2022/03/10–2025/08/29 Thesis: Thompson Sampling for Bandit Convex Optimization. Continuing in the PhD program at the University of Washington.

• Kushagra Chandak. Co-supervised with Nidhi Hegde. 2022/03/14–2023/11/21 Thesis: Differentially Private Algorithms for Efficient Online Matroid Optimization

• Vlad Tkachuk. 2022/01/01–2023/11/21 Thesis: On Efficient Planning in Large Action Spaces with Applications to Cooperative Multi-Agent Reinforcement Learning Continuing in the PhD program at the University of Alberta.

• Shuai Liu. 2022/03/14–2023/11/21. Thesis: Perturbed History Exploration in Stochastic Subgaussian Generalized Linear Bandits Continuing in the PhD program at the University of Alberta.

• Chang Liu. 2022/03/22-2023/11/21 Continuing at UCLA in the PhD program

• Valentin Tiriac. 2021/03/31-2024/08/01 (sadly, did not finish)

• Connor Stephens. 2020/03/18–2023/06/14. Present position: Machine Learning Scientist in biomolecule design at Lila Sciences.

• Yue (Anna) Gao. 2018-2021. Present affiliation: Superhuman. Previously an AI Research Scientist at Quincus and a Senior Machine Learning Engineer at Keebo.

• Alex Ayoub. 2020/02/21–2021/11/19. Continued in and completed the PhD program; see above. Thesis: Toward Sample Efficient Reinforcement Learning with Function Approximation

• Dong Wang, co-supervised with Ilbin Lee. (2020-2021). Thesis: Optimized Batch Policy Evaluation in the Presence of Monotone Responses

• Mikhail Konobeev (2019-2021); finished while working with Martha White. Position after graduation: PhD student, Lausanne, Switzerland.

• Shun Jie Lau (2012-2018). Present position: Software Developer at CEMWorks Inc.

• Xiaowei Hu, 2015 Jan 1-2016 December 20
  Thesis: Bandit Convex Optimization with Biased Noisy Gradient Oracles. Present position: S.E. at Microsoft, Vancouver.

• Yifan Wu, 2014 March 13-2016 August 31, co-supervised with András György
  Thesis: Online Learning under partial feedback.
  Co-winner of the Outstanding MSc Thesis Award, Dept. of CS, U. of A, 2016. 2017 Master's Thesis Award of the Canadian Artificial Intelligence Association. Present position: Research Developer at Headlands Technologies. Previously completed a PhD in Machine Learning at CMU.

• Roshan Shariff, 2012 March 26-2015 June
  Thesis: Exploiting Symmetries to Construct Efficient MCMC Algorithms with an Application to SLAM.
  Winner of the Outstanding MSc Thesis Award, Dept. of CS, U. of A.
  Position after graduation: Continuing in the PhD program.

• Hao Cheng, 2012 April 1-2013 September 20, co-supervised with Dale Schuurmans.
  Thesis: Bregman Divergence Clustering: A Convex Approach.
  Nominated for Outstanding MSc Thesis Award, Dept. of CS, U. of A
  Position after graduation: PhD student at the University of Washington

• Jamie Kiros, 2012 March 28-2013 June 5,
  Thesis: Learning Deep Representations, Embeddings and Codes from the Pixel Level of Natural and Medical Images.
  Winner of the Outstanding MSc Thesis Award, Dept. of CS, U. of A.
  Position after graduation: PhD student at the University of Toronto.

• Navid Zolghadr, 2011 April 15- 2013 January 30. co-supervised with Russ Greiner
  Thesis: Probe-Efficient Learning.
  Present position: Software Developer at Verily.

• Mohammad Ajallooeian, 2011 March 21-2013 January 31, co-supervised with András György
  Thesis: Optimal Mechanisms for Machine Learning: A Game-Theoretic Approach to Designing Machine Learning Competitions.
  Position after graduation: Continued in the PhD program.

• Pooria Joulani, 2011 March 31- 2012 September 26, co-supervised with András György.
  Thesis: Multi-Armed Bandit Problems under Delayed Feedback.
  Nominated for Outstanding MSc Thesis Award, Dept. of CS, U. of A.
  Position after graduation: Continued in the PhD program.

• Bernardo Avila Pires, 2009-2011.
  Thesis: Statistical analysis of L1-penalized linear estimation with applications.
  Nominated for Outstanding MSc Thesis Award, Dept. of CS, U. of A.
  Position after graduation: Continued in the PhD program.

• Yasin Abbasi-Yadkori
  Thesis: Forced-Exploration Based Algorithms for Playing in Bandits with Large Action Sets 2008.
  Position after graduation: Continued in the PhD program.

• Varun Grover,
  Thesis: Active Learning and its Application to Heteroscedastic Problems (2008),
  Position after graduation: Systems Analyst, City of Edmonton.

• Gergely Neu BME,
  Thesis: Inverse Reinforcement Learning and Its Application to Learning to Parse.
  Position after graduation: Continued in the PhD program at BME, see above.

• Volodymyr Mnih Thesis: Efficient Stopping Rules.
  Present position: Research Scientist at Google DeepMind. Previously completed a PhD in Machine Learning at the University of Toronto.

• Zoltán Kőmíves ELTE; co-supervised with András György 2007.
  Position after graduation: IT Consultant at SK Point. Present affiliation: Spire, Glasgow.