Monte Carlo methodology
Parallel & distributed algorithms
Scalable data analysis
I am a Computational Statistician in the School of Mathematics at the University of Bristol.
My research is primarily in the area of stochastic algorithms for approximating intractable quantities that arise in data analysis. Examples of such algorithms are Markov chain and Sequential Monte Carlo. I work on both theory and methodology: research in this area is interdisciplinary, bringing together advances in applied probability, algorithms, and statistics.
I am often interested in algorithms that scale well in parallel and distributed computing environments, and in computational and statistical trade-offs when conducting inference.
I am an investigator on the Computational Statistical Inference for Engineering and Security (CoSInES) EPSRC programme grant, and the "Advances in Sequential Monte Carlo Methods for Complex Bayesian Models" ARC Discovery Projects grant.
Associate Editor, Statistics and Computing.
Associate Editor, Journal of Computational and Graphical Statistics.
Associate Editor, Journal of Machine Learning Research.
Associate Editor, Foundations of Data Science.
Programme Director, Data Science at Scale, Alan Turing Institute.
Associate Professor (Reader) in Statistical Science, University of Bristol, 2019-20
Senior Lecturer in Statistical Science, University of Bristol, 2018-19
Lecturer in Statistical Science, University of Bristol, 2017-18
Turing Fellow, Alan Turing Institute, 2016--2017.
Assistant Professor, University of Warwick, 2013--2017.
CRiSM Research Fellow, University of Warwick, 2011--2013.
School of Mathematics
Bristol BS8 1UG
Email: anthony.lee "at" bristol.ac.uk
Office in Fry: GA.03
Please note: I receive a reasonably large volume of unsolicited emails, and I cannot reply to all of them.