Our Group

We love Causal Inference!

Principal Investigator

• Robin J. Evans: Causal inference, especially combining different data modalities and simulation. Graphical models and latent variable models. Google Scholar

Postdoctoral Researcher

• Jakob Zeitler: Causal inference, partial identification, active learning and Bayesian optimisation. Google Scholar

DPhil Students

• Xi Lin: Data fusion, causal simulation. Google Scholar
• Daniel Manela: Copulas, causal simulation. Google Scholar
• Linying Yang: Distribution shift, robustness in causal inference. Google Scholar
• Yasin Ibrahim: Causal generative models for medical imaging. Google Scholar
• Alex Gruen: Data fusion, causal simulation.
• Ruizi Yan: Generative models, combining data sets.

Alumni

• Jake Fawkes: Thesis: Data Quality in Causal Machine Learning with Applications to Algorithmic Fairness (2025), Kernel-based causal inference, fairness Google Scholar
• Ryan Carey: Thesis: Constraints on Agents in Causal Models (2024), Quantitative Researcher, Optiver
• Zhongyi Hu: Thesis: Causal Discovery with Ancestral Graphs (2023), Postdoctoral researcher at Unversiteit van Amsterdam, supervised by Stephanie van der Pas.
• Robert Hu: Thesis: Large Scale Methods for Kernels, Causal Inference and Survival Modelling (2023), Researcher at Graphcore
• Bohao Yao: Thesis: Algebraic Properties of Linear Structural Equation Models (2022)
• Adrien Hitz Thesis: Modelling of Extremes (2017)