Summary
Christopher Nemeth is a Professor in Probabilistic Machine Learning and Co-Director of the Data Science Institute at Lancaster University, with 11 years of academic experience bridging Bayesian machine learning and computational statistics. He leads a UKRI-EPSRC Turing AI Fellowship (PASCAL) focused on probabilistic, scalable algorithms and previously held an EPSRC Innovation Fellowship addressing security and location-data challenges. His work centres on MCMC, SMC, Gaussian processes and statistical network modelling, with a current emphasis on gradient flow methods to develop scalable optimisation and sampling algorithms for large datasets. Based in Lancaster and grounded in a PhD in Statistics, he combines deep theoretical expertise with applied problem solving, notably pushing computable approaches that balance exactness and scalability.
11 years of coding experience
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at The University of Manchester
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at Lancaster University