Lawrence Bull [PhD]

Research Fellow in machine learning for physical systems [Phy-ML] at the University of Glasgow. Always trying to encode structure into machine learning, to better reflect our scientific knowledge. Applied to condition monitoring and emulation, from rail bridges to peat bogs!

[Bio]

[May.2024-May.2029] University of Glasgow | Research Fellow | Centre for Data Science (2026-2029) Statistics & Data Analytics (2024-2026)

[Sep.2022-May.2024] University of Cambridge | Research Associate | Computational Statistics and Machine Learning Group | Department of Engineering

[Jul.2021-Sep.2022] The Alan Turing Institute | Research Associate | Data-Centric Engineering

[Sep.2016-Jun.2021] University of Sheffield | Research Assistant (2019-2021) PhD Student (2016-2019) | Dynamics Research Group | Department of Engineering

[Research projects]

Integrating telemetry data with applied mathematics, to improve systems understanding.

[2026] (PI) Uncertainty Quantification for Adaptive Emulators | w/ Tim Rogers, Vinny Davies | DTnet+ pilot project [£48k]

[2025] (PI) Scaling Cardiac Models by Super-Resolution | w/ William Ryan, David Dalton | SoftTMech feasibility project [£13k]

[2023] (CI) Staffordshire Rail Bridge Digital Twin: Phase III | w/ Miguel Bravo Haro | Trimble Fund of Cambridge University [£25k]

[PhD + Post-doc] Semi-supervised and population-based structural health monitoring: planes, trains, automobiles, and wind turbines. Supervisors: Keith Worden, Nikos Dervilis, Mark Girolami

[PhD supervision]

[External standing]

Engineer at the data-centric engineering consultancy AQ, Editor for the Data-Centric Engineering journal, and member of Statistical Engineering Group of the Royal Statistical Society. Previously on the Early-Career Academic and Professionals Panel (2021-2023) for the Cambridge Centre for Smart Infrastructure and Construction (CSIC).