Dr Henry Moss
Reader in Mathematics and AIResearch Interests
I work on probabilistic machine learning for scientific discovery and engineering design, in settings where every experiment is slow, costly, or both. My group, Mathematical AI for Decision and Discovery, builds models that decide what to measure next and that can absorb what scientists already know about a system.
Much of our current work develops Gaussian process flows, which recast Gaussian process sampling as a generative flow. This gives a general mechanism for incorporating the full richness of real-world knowledge as conditioning information, from governing physics and hard constraints to descriptions in natural language, rather than relying on measurements alone. Alongside this we work on Bayesian optimisation, active learning and experimental design.
We work closely with industry on problems ranging from drug discovery to fusion reactor design, climate modelling and materials discovery. See my website for more info (https://henrymoss.github.io/)
PhD Supervision Interests
I welcome PhD students across probabilistic machine learning and its scientific applications. On the methodological side I supervise work on Gaussian processes, Bayesian optimisation (particularly in high dimensions) and generative modelling, including diffusion and flow matching. My students apply these to drug discovery and biologics, fusion reactor design, climate and weather, oceanography, materials, molecular design, quantum devices and aerospace engineering. I am happy to supervise projects that are mainly mathematical, mainly applied, or a mixture, and I particularly welcome projects shaped with an industrial partner.
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DSI: Determination of Tropical Oxidising Capacity through model calibration (DeTOX)
01/04/2026 → 30/09/2029
Research
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MARS: UKAEA studentship top-up
01/10/2025 → 30/09/2029
Research
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MARS: IceDice: Predicting the stochastic behaviour of West Antarctica’s Marine Ice Sheet
01/09/2025 → 31/08/2028
Research
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MARS: G-Research PhD Studentship (Abiel Talwar)
01/01/1900 → …
Research
The Magic of Maths
Public Lecture/ Debate/Seminar
Greenhead College
School Engagement
Pint of Science
Participation in conference - Public
Highly Structured Bayesian Optimization
Invited talk
Highly structured Bayesian Optimization
Invited talk
To Bayes Opt and Beyond
Invited talk
Gaussian Process Summer SChool
Participation in workshop, seminar, course
Return of the Latent Space Cowboys
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Experimental Design in the Age of GenAI
Invited talk
Fusing Neural and Statistical Models
Invited talk
Return of the Latent Space Cowboys
Invited talk
Return of the Latent Space Cowboys
Invited talk
Return of the Latent Space Cowboys
Invited talk
Gaussian Process Summer School
Other
Sargent Center Summer School, Imperial College
Participation in workshop, seminar, course
So you have an emulator, so what?
Invited talk
Return of the Latent Space Cowboys
Invited talk
MARS: Mathematics for AI in Real-world Systems
MARS: Mathematics for AI in Real-world Systems
MARS: Mathematics for AI in Real-world Systems
STOR-i Centre for Doctoral Training
- Centre of Excellence in Environmental Data Science
- MARS: Mathematics for AI in Real-world Systems
- Statistical Artificial Intelligence
- STOR-i Centre for Doctoral Training