About
Dr Henry Moss is a Researcher at the Department of Applied Mathematics and Theoretical Physics within the School of Physical Sciences at the University of Cambridge. His work focuses on machine learning applications in climate modeling, Bayesian optimization, and Gaussian processes, bridging computational mathematics with environmental science and chemistry.
His research interests include:
- Bayesian optimization for environmental and chemical systems
- Reinforcement learning in climate modeling
- Gaussian processes for molecular property prediction
- High-throughput machine learning in scientific domains
- Interpretable AI for coastal flooding prediction
- Hybrid ML-physics modeling
Dr Moss's publications highlight his contributions to federated learning for climate models, sparse Gaussian process techniques, and multi-objective optimization frameworks. These works span applications in weather prediction, chemical engineering, and oceanography.
Email: hwm26@cam.ac.uk
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