About

I am a Group Leader for Biomedical Machine Learning at the MRC Biostatistics Unit, University of Cambridge, where I am establishing a research programme at the interface of statistics and machine learning. My current work focuses on biomedical applications, with particular interest in generative models for time-dependent data, latent dynamics through manifold learning, and the development of robust AI systems grounded in scientific, geometric, and mathematical principles.

Prior to joining the BSU, I was a Senior Research Scientist in the Biomedical Image Computing Group at ETH Zürich, leading projects on generative modelling, CT radiomics, and MRI super-resolution. I have also held research positions at the Institute of Astrophysics, ETH Zürich, and obtained a doctorate in Computational and Theoretical Physics from ETH Zürich. My undergraduate and master's degrees in Physics are from the University of Cambridge.

An up-to-date list of my publications is available on my Google Scholar profile.

Research Interests

• Spatio-temporal dynamics and forecasting
• Medical imaging (Computed Tomography, Radiomics, Super-Resolution)
• Biostatistics (Genomics, Epidemiology)
• Generative modelling and AI (Gradient flows, Normalizing Flows, VAEs, Diffusion Models)
• Differential geometry and theoretical physics
• Fluid–structure interaction and Lattice Boltzmann methods
• Quantum machine learning

Education

• PhD, Computational & Theoretical Physics — ETH Zürich, 2015–2021.
  Thesis: Flow and Dirac Particles on Curved and Topological Manifolds.
• Master of Science, Part III (First Class) — University of Cambridge, 2013–2014.
  Particle Physics, Relativistic Cosmology, Gauge Field Theory, Non-Linear Optics.
• Bachelor of Science — Univers