Michael Pitt

Professor Michael Pitt is a faculty member in the Department of Mathematics at King's College London, holding the rank of Professor of Statistics within the Faculty of Natural, Mathematical & Engineering Sciences. He completed his doctorate in Statistics at the University of Oxford (Nuffield College) in 1997, followed by postdoctoral research at Imperial College London. His career includes roles at the University of Warwick (1999-2016) as Assistant and Associate Professor before joining King's College.

Education:

• PhD in Statistics, University of Oxford (1997)
• Postdoctoral Research, Imperial College London (1997-1999)

Research Interests: Focuses on advanced statistical methodologies including particle filtering, sequential Monte Carlo (SMC), Markov chain Monte Carlo (MCMC), and their applications in financial econometrics and biostatistics. Key areas include:

• Development of computationally efficient algorithms for Bayesian inference
• Analysis of financial time series and stochastic volatility models
• Multivariate copula models for dependence structures
• Clinical outcome analysis in cardiology through statistical revascularization studies

Publications: Recent work emphasizes methodological advancements in pseudo-marginal methods, correlated particle filtering, and adaptive sampling techniques. Notable contributions include applications in cardiac clinical outcomes and high-dimensional density modeling.

Labs/Teams: Active member of the Research Centre for Non-Equilibrium Science (CNES), focusing on interdisciplinary non-equilibrium systems, and part of the Statistics Group within the Department of Mathematics.