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Mengran Li

Postdoctoral Research Associate Smith School of Enterprise and the Environment, University of Oxford
Extreme value theory | Causal inference

I am a Postdoctoral Research Associate at the University of Oxford. My research develops causal inference methodology for rare and extreme events, spanning causal discovery, extreme treatment effects, and climate event attribution. By combining causal inference with extreme value theory, I aim to support reliable decision-making in high-impact settings such as climate risk.

📢 Update: I joined the Smith School of Enterprise and the Environment at the University of Oxford in August 2026.

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Academic Appointments

Postdoctoral Research Associate

2026 – Present

Education

Doctor of Philosophy in Statistics

University of Glasgow · Glasgow, UK
2022 – 2026
Thesis: Causal Inference in the Tails: Extreme Event Attribution, Treatment Effects, and Structural Discovery. Supervised by Dr. Daniela Castro-Camilo.

Master of Science in Statistics (with Distinction)

University of Glasgow · Glasgow, UK
2020 – 2021
Dissertation: Spatiotemporal modelling and prediction of average flows in Scotland based on generalized additive models.

Bachelor of Science in Statistics (Major) and Finance (Double Major)

2015 – 2019
Completed Bachelor’s degrees with a strong foundation in probability, statistical inference, and mathematical statistics.

Research

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Causal discovery in multivariate extremes

 Tail-induced asymmetry enables causal structure learning in high-dimensional multivariate extremes. We develop methods that exploit directional information encoded by tail dependence patterns to recover causal graphs in extreme regimes.
Apr 1, 2026
3 min read

Extreme quantile treatment effect (EQTE)

 Extreme quantile treatment effects (eQTEs) measure causal impacts on outcome distribution tails. We propose the TIEE framework combining information across quantile levels with extreme value models, enabling causal inference for rare, high-impact events in environmental risk, economics, and public health.
Oct 1, 2025
3 min read

Extreme Event Attribution (EEA)

 Exploring how tail assumptions influence attribution of extreme climate events, combining simulation, spatial methodology, and software development.
Jul 1, 2025
4 min read

Wee Extremes: EVA 2023 Data Challenge

 Statistical Methodology for Extreme Event Risk Assessment in the EVA 2023 Data Challenge.
May 30, 2023
2 min read