Academic

Research Interests

• Probabilistic Machine Learning - Gaussian Processes, Bayesian Deep Learning
• Uncertainty Quantification - Propagating uncertainty through models and decisions
• Data-Driven Process Control - Model Predictive Control with learned models

Publications & Reports

View on Google Scholar

• Learning with Embedded Linear Equality Constraints via Variational Bayesian Inference
  M. Marsh, , B. Chachuat, A. Del Rio Chanona
  AISTATS 2026 Workshop, OPTIMAL: Optimisation and Post Bayesian Inference in Machine Learning, 2026. [PDF] — Workshop Paper

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Current Research

I’m currently working on developing new algorithms for modelling and controlling Process Systems under uncertainty, with a focus on constraint satisfaction and safety guarantees.

Supervisors:

• Dr. Antonio Del Rio Chanona
• Prof. Benoit Chachuat

Affiliation: OptiML PSE Group, Imperial College London