|Position||Lecturer (Assistant Professor)|
|Phone (external)||020 3108 4472|
|Themes||Biostatistics, General Theory and Methodology, Computational Statistics|
Before joining UCL as a Lecturer at the beginning of 2022, Brieuc was a postdoctoral research associate in statistical machine learning at the Big Data Institute and the Department of Statistics at the University of Oxford, working with Prof Chris Holmes and Prof Gil McVean. Brieuc was also a Junior Research Fellow in Statistics at Jesus College, Oxford. Brieuc completed his PhD at the MRC Biostatistics Unit, University of Cambridge under the supervision of Dr Simon White, Prof Rik Henson and Dr Linda Geerligs.
Brieuc's primary research area is health data science, with a focus on statistical methods of health equity. He is particularly interested in developing and applying novel Bayesian statistical methodology for biomedical data. Recent applications include COVID-19 and polygenic scores.
- A predictive approach to Bayesian nonparametric survival analysis (AISTATS.2022)
E.Fong, B. Lehmann
- Improving local prevalence estimates of SARS-CoV-2 infections using a causal debiasing framework (Nature Microbiology,2021)
G. Nicholson, B. Lehmann, T. Padellini, K.B. Pouwels, R. Jersakova, J. Lomax, R.E. King, A. Mallon, P.J. Diggle, S. Richardson, M. Blamgiardo, C.C. Holmes
- Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models (Neurolmage, 2021)
B. Lehmann, R.N. Henson, L. Geerligs, Cam-CAN, S.R. White