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Zonghao (Hudson) Chen
Ph.D. candidate, University College London

About me

I am a Ph.D. candidate at the Center of Foundational Artificial Intelligence of University College London, supervised by François-Xavier Briol and Arthur Gretton. I am interested in understanding machine learning algorithms through the dual lenses of optimization and generalization. My current research focuses on generative models, Monte Carlo methods, and causal inference. Prior to my PhD, I obtained my bachelor's degree from the department of Electronic Engineering, Tsinghua University, 2022.
I organize the JumpTrading/ELLIS CSML seminar series on Computational Statistics and Machine Learning for the UCL ELLIS Unit. Feel free to drop me an email if you would like to give a talk!

Recent News

November 2025





June 2025

Two new journal papers on nonparametric instrumental variables (NPIV) just came out! 🎉 One Paper studies convergence guarantees under neural network representations, and the other Paper establishes sharp statistical rates for kernel-based estimators.

I will visit Taiji Suzuki at RIKEN AIP and University of Tokyo from June 2025 to August 2025.

Journal Publications and Preprints

  • (De)-regularized Maximum Mean Discrepancy Gradient Flow
    Zonghao Chen, Aratrika Mustafi, Pierre Glaser, Anna Korba, Arthur Gretton, Bharath K. Sriperumbudur
    JMLR '25 Journal of Machine Learning Research
    Paper, Code, Poster

  • Towards a Unified Analysis of Neural Networks in Nonparametric Instrumental Variable Regression: Optimization and Generalization
    Zonghao Chen, Atsushi Nitanda, Arthur Gretton, Taiji Suzuki
    Preprint
    Paper, Code,

  • Nonparametric Instrumental Variable Regression with Observed Covariates
    Zikai Shen*, Zonghao Chen*, Dimitri Meunier, Ingo Steinwart, Arthur Gretton†, Zhu Li†
    Preprint
    Paper
  • Conference Publications and Preprints

  • Stationary MMD Points for Cubature
    Zonghao Chen, Toni Karvonen, Heishiro Kanagawa, François-Xavier Briol, Chris. J. Oates
    Preprint
    Paper, Code

  • Nested Expectations with Kernel Quadrature
    Zonghao Chen, Masha Naslidnyk, François-Xavier Briol
    ICML '25 International Conference on Machine Learning
    Paper, Code, Poster

  • Conditional Bayesian Quadrature
    Zonghao Chen*, Masha Naslidnyk*, Arthur Gretton, François-Xavier Briol
    UAI '24 Conference on Uncertainty in Artificial Intelligence
    Paper, Code, Poster

  • Conformal Counterfactual Inference under Hidden Confounding
    Zonghao Chen*, Ruocheng Guo*, Jean-François Ton, Yang Liu
    KDD '24 Conference on Knowledge Discovery and Data Mining
    Paper, Code, Poster

  • Tractable Function-Space Variational Inference in Bayesian Neural Networks
    Tim G. J. Rudner, Zonghao Chen, Yee Whye Teh, Yarin Gal
    NeurIPS '22 Conference on Neural Information Processing Systems.
    Paper

  • Efficient Neural Network Training via Forward and Backward Propagation Sparsification
    Xiao Zhou*, Weizhong Zhang*, Zonghao Chen, Shizhe Diao, Tong Zhang
    NeurIPS ’21 Conference on Neural Information Processing Systems
    Paper

  • A Neural Tangent Kernel Perspective on Function-Space Regularization in Neural Networks
    Zonghao Chen*, Xupeng Shi*, Tim G. J. Rudner, Qixuan Feng, Weizhong Zhang, Tong Zhang
    NeurIPS 2022 Workshop: Optimization for machine learning
    Paper

  • Awards

    • RIKEN Visiting Fellowship in Machine Learning, RIKEN AIP, Japan

    • Newcastle Visiting Fellowship in Machine Learning, Newcastle University

    • Tsinghua Presidential Scholarship, Tsinghua University

    • Yinghua Scholarship, Tsinghua University

    Valar Morghulis! Valar Dohaeris!