Hi, I’m Peter and I live in London. I’m a theoretical physicist, migrated into machine learning. My main research interests at the moment are in physics-informed mahcine learning, operator learning and applied probability. I presently am one of eleven Turing Research Fellows at The Alan Turing Institute. I also am an Honorary Fellow at Imperial College London.

Before that, I was a research associate at The Alan Turing Institute, working with Andrew Duncan on scalable methods for statistical inference and machine learning. And before even that, I worked in classical statistical mechanics of soft matter, developing models of interface motion and phase transitions. I did my PhD at Imperial College London, in the area of computational methods for PDEs, arising in classical density functional theory. My PhD thesis supervisor was Serafim Kalliadasis.

Academic CV Teaching Statement
Preferred Stack
  • JAX/PyTorch/TensorFlow
  • NumPyro/Pyro/PyMC3/Stan
  • GPy
  • FEniCS
  • Python/MATLAB/Julia/C++