About Me

I am a PhD student in Machine Learning at University of Cambridge (Machine Learning Group, Computational and Biological Learning Lab) and Max Planck Institute for Intelligent Systems (Empirical Inference Department), under the Cambridge-Tübingen PhD Fellowship in Machine Learning. My supervisors are Professor José Miguel Hernández-Lobato and Professor Bernhard Schölkopf. My advisor is Dr Hong Ge.

I am keen on basic research in machine learning and its scientific applications (e.g., drug discovery). My research interest lies at the intersection of probabilistic methods, deep learning, and causal inference. I aim to develop data-efficient and causally-aware machine learning methods that enable active data collection, robust inference and prediction, efficient data compression, and realistic generation of novel synthetic data.

  • Probabilistic Modelling
  • Deep Learning
  • Representation Learning
  • Multi-task/Meta Learning
  • Generative Modelling
  • Optimization
  • Causal Modelling
  • PhD in Machine Learning

    University of Cambridge and Max Planck Institute for Intelligent Systems

  • MPhil in Machine Learning and Machine Intelligence, Distinction, 2021

    University of Cambridge

  • BSc in Mathematics, First Class Honours, 2020

    University of Manchester


See also my Google Scholar profile or search on my publication page.
(2022). Optimal Client Sampling for Federated Learning. TMLR 2022.

PDF Cite Code Video OpenReview arXiv

(2022). An Evaluation Framework for the Objective Functions of De Novo Drug Design Benchmarks. ICLR 2022 MLDD Workshop.

PDF Cite OpenReview

(2021). Causal Representation Learning for Latent Space Optimization. MPhil Thesis, University of Cambridge.

PDF Cite

(2020). To Ensemble or Not Ensemble: When Does End-to-End Training Fail?. ECML 2020.

PDF Cite Code Video Springer Link arXiv


Doctoral Fellow - Machine Learning
Oct 2021 – Present Cambridge, England, United Kingdom
Cambridge-Tübingen PhD Fellow in Machine Learning, funded by a Cambridge Trust Scholarship and a CUED PhD Studentship.
Doctoral Fellow - Machine Learning
Oct 2021 – Present Tübingen, Baden-Württemberg, Germany
Cambridge-Tübingen PhD Fellow in Machine Learning.
Research Assistant - Probabilistic and Causal Machine Learning
Jan 2021 – Sep 2021 Cambridge, England, United Kingdom
Research Intern - Federated Learning and Distributed Optimization
Aug 2020 – Sep 2020 Remote
Research Assistant - Ensemble Deep Learning
Sep 2018 – Jun 2020 Manchester, England, United Kingdom
Research Engineer Intern - Deep Learning on Edge Devices
Jun 2019 – Aug 2019 Kings Langley, England, United Kingdom


Cambridge-Tübingen PhD Fellowship in Machine Learning
The Royal Statistical Society Prize
International Mathematics Scholarship


  • wc337@cam.ac.uk
  • St Edmund’s College, Cambridge, Cambridgeshire CB3 0BN, United Kingdom