I am a Cambridge-Tübingen Fellow at the Max Planck Institute for Intelligent Systems and the University of Cambridge, supervised by Bernhard Schölkopf and Ferenc Huszár. Previously I worked on fairness with Ricardo Silva at UCL and variable selection in high-dimensional statistics with Richard Samworth.

My research interests are on scientific induction (a.k.a causality) and non-i.i.d. data. I am interested in incorporating causality in machine learning models and understanding causality in non-i.i.d. data: from Causal de Finetti (NeurIPS 2022) to Do Finetti, from out-of-distribution to out-of-variable (ICLR 2023).

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I take great pleasure in (co-)mentoring a few talented and highly motivated students. It has been a great privilege for me to constantly learn and get inspired by them. Here is a list of students I am working with in time-wise order:

  • Anna Kerekes, PhD student at ETH Zurich, Feb 2024 - now
  • Szilvia Ujváry, PhD student at Cambridge, Feb 2024 - now
  • Davin Xianjun Choo, PhD student at NUS, Jun - Aug 2023

Application For motivated students interested in working on causality and / or machine learning, feel free to reach out via Internship is possible to be hosted at beautiful MPI.

  • Causality
  • Scientific Induction
  • Machine Learning
  • Non-I.I.D. Data
  • PhD in Computer Science, 2021

    University of Cambridge & Max Planck Institute for Intelligent Systems

  • Msc in Machine Learning, 2020

    University College London

  • Bachelor and Master in Mathematics, 2015

    University of Cambridge

Recent Publications

(2023). Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. In Advances in Neural Information Processing Systems (NeurIPS), 2023.

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(2023). Out-of-Variable Generalization for Discriminative Models. arxiv preprint 2304.07896.

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(2023). Dataflow graphs as complete causal graphs. In IEEE/ACM 2nd International Conference on AI Engineering–Software Engineering for AI (CAIN), 2023.

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(2023). On the Interventional Kullback-Leibler Divergence. In 2nd Conference on Causal Learning and Reasoning (CLeaR), 2023.

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(2022). Pragmatic Fairness: Optimizing Policies with Outcome Disparity Control. In NeurIPS 2022 Workshop on Algorithmic Fairness through the Lens of Causality and Privacy.

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Dean’s List
Premium Research Bursary
Awarded £15,609
Cambridge Tübingen PhD Fellowship in Machine Learning
Awarded ~ £168,249
Openshaw Prize, Exhibition & Foundation Scholarship

Recent & Upcoming Talks


Intern Mentoring
Max Planck Institute for Intelligent Systems
June 2023 – August 2023 Germany
Mentoring Xianjun Davin Choo during his intern period at MPI on out-of-variable generalization.
Workshop Organizer
April 2023 – April 2023 Germany
Workshop Organizer
January 2023 – January 2023 Spain