Harrison Wilde

Harrison Wilde is a fourth-year PhD student in the Department of Statistics at the University of Warwick, supervised by Sebastian Vollmer at the German Research Center for Artificial Intelligence (DFKI). He holds an honorary Research Fellow position at the UCL Institute of Health Informatics and collaborates with institutions such as Oxford, Wellcome Trust, and the Alan Turing Institute. His research focuses on Bayesian and causal computation, synthetic data generation, and applications in epidemiology, pharmaceuticals, public health, and fairness/privacy in data science.

Wilde's research explores the statistical properties of models trained on synthetic data, with a particular emphasis on privacy, fairness, and robust Bayesian updating. He has contributed to projects like the Turing PPL, CVD-COVID-UK, and COVID-IMPACT Consortia, and his work has been published in top journals like PLOS One, BMC Medicine, and BMJ Open.

His scientific awards include the

• Feuer International Scholarship in Artificial Intelligence (2019)
• Data Science for Social Good Fellowship (2019)

He has also been interviewed by the BBC Evening News and actively supports open science initiatives.

Wilde has taught modules including

• ST202: Stochastic Processes (2021-2022)
• ST346: Generalized Linear Models for Regression and Classification (2020-2021)
• ST104: Statistical Laboratory (2020-2021)
• CS118: Programming for Computer Scientists (2019-2021)

but took a temporary withdrawal from teaching during Term 1 of the 2021-2022 academic year while working at Twitter.

He is a core contributor to the Turing PPL and part of the CVD-COVID-UK and COVID-IMPACT Consortia, collaborating with teams like Chris Holmes’ Lab at Oxford and the Royal Statistical Society’s West Midlands Local Group.