Professor Christopher Nemeth

Professor in Statistics

Profile

My research is in the areas of computational statistics and probabilistic machine learning, specifically Markov chain Monte Carlo, sequential Monte Carlo, Gaussian processes and approximate Bayesian computation. Currently, as part of my UKRI fellowship, I am developing probabilistic AI algorithms for large-scale learning, with a focus on the mathematical foundations of these algorithms.

Applications of my research have an impact in a variety of areas, including target tracking, environmental science and econometrics.

Bayesian and Computational Statistics, Statistical Artificial Intelligence

Bayesian and Computational Statistics, STOR-i Centre for Doctoral Training

Bayesian and Computational Statistics, STOR-i Centre for Doctoral Training

Bayesian and Computational Statistics, STOR-i Centre for Doctoral Training

  • Bayesian and Computational Statistics
  • Centre of Excellence in Environmental Data Science
  • DSI - Foundations
  • Statistical Artificial Intelligence
  • STOR-i Centre for Doctoral Training