Hi, I’m Peter and I live in London. I’m a theoretical physicist, migrated into machine learning. My main research interests presently are in applied probability and computational statistics. I am currently a research associate at The Alan Turing Institute, working with Andrew Duncan on scalable methods for statistical inference and machine learning.

Before 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 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++