Dr Matthew Pryce

Biographical Details

Matt is a Postdoctoral Fellow in the Department of Statistical Science at UCL. He works with Prof. Karla Diaz Ordaz on methodological developments in causal machine learning, with a particular focus on estimating heterogeneous treatment effects. His research centres on methods for time-to-event data, especially in settings involving coarsened events and competing risks. He received his PhD from the London School of Hygiene & Tropical Medicine in 2025, during which he completed an internship at Novartis.

Research Interests

Causal machine learning, Heterogeneous treatment effects, Time-to-event data 

Selected Publications

Pryce, M., Diaz-Ordaz, K., Keogh, R.H. and Vansteelandt, S., 2025. Causal machine learning for heterogeneous treatment effects in the presence of missing outcome data. Biometrics, 81(3), p.ujaf098.

Pryce, M., Diaz-Ordaz, K., Keogh, R.H. and Vansteelandt, S., 2025. Targeted learning of heterogeneous treatment effect curves for right censored or left truncated time-to-event data. http://arxiv.org/abs/2603.26502