Dr Simon Driscoll
- Assistant Research Professor
About
Simon is an Assistant Research Professor in the Department of Applied Mathematics and Theoretical Physics and at the Institute of Computing for Climate Science, University of Cambridge. He holds undergraduate and postgraduate qualifications in pure mathematics and mathematical/computational modelling, and a PhD in Physics from the University of Oxford, where his doctoral research focused on dynamics, satellite observations, aerosols and radiative transfer. Most recently he held a position as Senior Research Associate at the Alan Turing Institute.
Simon is the lead author of a comprehensive textbook on artificial intelligence across climate and the environmental sciences, available in major bookstores throughout Europe and North America. His doctoral research featured in major European newspapers and books, and formed the basis of a documentary broadcast on Belgian national television. He has participated in public science discussions in multiple countries and conducted broader science communication activities throughout his career. He also serves as a scientific advisor to not-for-profit organisations.
His research sits at the interface of applied mathematics, physics, AI, climate science and, increasingly, econometrics. He is actively building collaborations across Europe, the United States, and Africa, and welcomes opportunities to work with academic, industry, and policy partners. His work is motivated by a commitment to advancing science for societal and environmental benefit.
Research
Research interests
- AI
- Econometrics
- Climate science
- Mathematical modelling
- Planetary science
- Exoplanetary science
Simon’s research spans applied mathematics (eg. applications of Koopman theory), mathematical modelling, mathematical physics (e.g. angular momentum), machine learning and artificial intelligence, climate science, volcanic eruptions, geoengineering, climate econometrics and migration. His work in climate modelling has included how models represent the atmospheric response to volcanic eruptions, geoengineering scenarios including modelling of abrupt shocks, and stratospheric and tropospheric dynamics following aerosol injections.
His work in AI, together with his students, has focused on the development of machine learning emulators of physical processes, hybrid physics-AI modelling, AI weather forecasting, and the application of foundation models for geophysical problems. This includes research on extreme events (such as heatwaves and cyclones), and more recently the application of AI forecasting systems to African weather, with implications for early warning and disaster risk reduction. Recent climate research includes cryospheric observations and remote sensing – spanning optical, synthetic-aperture radar, and passive microwave methods - alongside Arctic and Antarctic sea ice modelling and Antarctic glaciology.
A related strand of his research examines what deep learning weather models physically and dynamically encode - questions of interpretability, trust, explainability and improvement that sit at the boundary of AI and atmospheric science. This includes work on the evaluation and verification of AI forecasting systems. Alongside applied AI research, Simon engages with questions of AI and environmental sustainability, including the environmental impacts of large language models (spanning carbon emissions, water consumption, resource extraction, and embedded hardware costs) and the broader systemic risks of AI deployment, including indirect downstream impacts. This strand of work sits at the intersection of AI, sustainability and environmental policy. Prior to moving into AI, Simon almost switched to econometrics as a post-doc in Oxford and Potsdam, and is actively reviving these interests, alongside research on migration.
Teaching and supervision
Simon co-supervises 2 PhD students and 2 Master's/undergraduate students.