KIPS (Kernels and Information Processing Systems) research group is a subset of the larger Computational Statistics and Machine Learning (OxCSML) network within the Department of Statistics and we closely collaborate with other researchers in OxCSML. Our research spans a variety of topics at the interface between statistical methodology and machine learning, including:

  • Large-scale nonparametric and kernel methods,
  • Multiresolution data and weak supervision,
  • Robust machine learning: robustness to model misspecification, censoring, spatiotemporal confounding,
  • Measures of dependence and multivariate interaction, causal inference,
  • Meta learning, hierarchical and deep generative modelling.

DPhil Students (Oxford)

  • Shahine Bouabid

    kernel methods, Bayesian nonparametrics, deep learning, aerosol-cloud interaction

  • Valerie Bradley

    kernel methods, selection bias

  • Siu Lun Chau

    kernel methods, preference learning, causality, explainable AI

  • Jake Fawkes

    causality, fairness, domain generalisation

  • Veit Wild

    Bayesian nonparametrics, Gaussian processes, variational inference


  • Jovana Mitrovic, DPhil 2019, Thesis: Representation Learning with Kernel Methods (now Senior Research Scientist at DeepMind)
  • Ho Chung Leon Law, DPhil 2019, Thesis: Testing and Learning on Distributional and Set Inputs (now Quantitative Researcher at Citadel Securities)
  • Qinyi Zhang, DPhil 2020, Thesis: Kernel Based Hypothesis Tests: Large-Scale Approximations and Bayesian Perspectives
  • Zhu Li, DPhil 2021, Thesis: On the Properties of Random Feature Methods (now Postdoc at Gatsby Unit, UCL)
  • David Rindt, DPhil 2021, Thesis: Nonparametric Independence Testing and Regression for Time-to-Event Data (now Quantitative Researcher at GSA Capital)
  • Anthony Caterini, DPhil 2021, Thesis: Expanding the Capabilities of Normalizing Flows in Deep Generative Models and Variational Inference (now Machine Learning Scientist at Layer6 AI, Toronto)
  • Jean-Francois Ton, DPhil 2022, Thesis: Causal Reasoning and Meta Learning using Kernel Mean Embeddings (now Senior Research Scientist at TikTok)
  • Robert Hu, DPhil 2022, Thesis: Large Scale Methods for Kernels, Causal Inference and Survival Modelling (now Applied Scientist at Amazon)


Emiliano Diaz Salas Porras, Oct-Dec 2019
Julien Lenhardt, May-Jun 2022

KIPS in November 2018 (from left to right): Robert Hu, Dino Sejdinovic, Ho Chung Leon Law, David Rindt, Anthony Caterini, Zhu Li, Qinyi Zhang, and Jean-Francois Ton.