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Simon Cotter

Professor in Applied Mathematics



What are your research interests?

I am interested in the development of theory and numerical methods for the solution of Bayesian inverse problems, with applications in biology, physics, materials, engineering and data analytics.

What is the focus of your current research?

Currently I am working on “Bayesian data selection”, an approach to Bayesian inverse problems that can more accurately fit models to data where there are corrupted data or regions with significant model-data mismatch.

What are some projects or breakthroughs you wish to highlight?

We are about to publish a preprint where we have used Bayesian data selection for the solution of an unlabelled landmark matching problem, which enables biologists to match up data from multiple image modalities on the single cell level in order to learn about factors in cell differentiation in embryonic development.

What memberships and awards do you hold/have you held in the past?

I am a member of the LMS and SIAM, and have held research funding from EPSRC and InnovateUK.

What is the biggest challenge in Data Science and AI right now?

Making AI a useful and safe tool in healthcare.

What real world challenges do you see Data Science and AI meeting in the next 25 years?

I’m not sure there are many limits as to what could potentially be achieved on the time scale of 25 years. I think that a major challenge will be the application of AI to environmental and sustainability challenges, including making AI and DS sustainable themselves.


Find out more about Simon’s research at Research Explorer.