Professor Mark Girolami
Mark Girolami joined the Department in January 2014 as a Professor of Statistics. He holds an honorary professorship in Computer Science at Warwick, is an EPSRC Established Career Research Fellow (2012 - 2017) and previously an EPSRC Advanced Research Fellow (2007 - 2012). He is also honorary Professor of Statistics at University College London, is the Director of the EPSRC funded Research Network on Computational Statistics and Machine Learning and in 2011 was elected to the Fellowship of the Royal Society of Edinburgh when he was also awarded a Royal Society Wolfson Research Merit Award.
He is currently seconded to the Executive Board of the Alan Turing Institute for Data Science as University Liaison Director based at the British Library in London. He has been nominated by the IMS to deliver a Medallion Lecture at JSM 2017.
His research and that of his group covers the investigation and development of advanced novel statistical methodology driven by applications in the life, clinical, physical, chemical, engineering and ecological sciences. He also works closely with industry where he has several patents leading from his work on e.g. activity profiling in telecommunications networks and developing statistical techniques for the machine based identification of counterfeit currency which is now an established technology used in current Automated Teller Machines. At present he works as a consultant for the Global Forecasting Team at Amazon in Seattle
He is joint Chair of the The Sixth IMS-ISBA Joint Meeting on Bayesian Computation
Probabilistic Numerics - what all the cool kids are up to these days.
Mike Betancourt, Simon Byrne, Sam Livingstone, and Mark Girolami (2016) "The Geometric Foundations of Hamiltonian Monte Carlo" to appear Bernoulli
Seppo Virtanen, Mattias Rost, Alistair Morrison, Matthew Chalmers, and Mark Girolami. (2016) Uncovering smartphone usage patterns with multi-view mixed membership models. Stat.
Oates CJ, Girolami M. (2016) Control Functionals for Quasi-Monte Carlo Integration. Nineteenth International Conference on Artificial Intelligence and Statistics (AISTATS), [arXiv] [Selected for Oral Presentation]
Gracie, K; Moores, M; Smith, W; Harding, K; Girolami, M; Graham, D; Faulds, K. (2016) Preferential Attachment of Specific Fluorescent Dyes and Dye Labelled DNA Sequences in a SERS Multiplex. to appear Analytical Chemistry
Shiwei Lan, Tan Bui-Thanh, Mike Christie, Mark Girolami (2016)
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems, Journal of Computational Physics Vol. 308, 81 - 101.
Briol, F-X., Oates, C. J., Girolami, M., & Osborne, M. A. (2015). Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees. Advances In Neural Information Processing Systems (NIPS) 2015.
Probability Measures for Numerical Solutions of Differential Equations P. Conrad, MAG, S.Sarkka, A.M.Stuart, K.Zygalkis.
Probabilistic Numerics and Uncertainty in Computations. Hennig, P., Osborne, M. A., & Girolami, M. Proceedings of the Royal Society A, Proc. R. Soc. A 2015 471 20150142; DOI: 10.1098/rspa.2015.0142.
On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods with Anne-Marie Lynne, Heiko Strathmann, Daniel Simpson and Yves Atchade. Statistical Science, Volume 30, Number 4 (2015), 443-467, 2015.
Seppo Virtanen, Mattias Rost, Matthew Higgs, Alistair Morrison, Matthew Chalmers and Mark Girolami. Non-parametric Bayes to infer playing strategies adopted in a population of mobile gamers (pages 46–58)
STAT, Article first published online: 4 MAR 2015 | DOI: 10.1002/sta4.75
New paper: with Chris Oates and Nicolas Chopin "Control Functionals for Monte Carlo Integration"
New paper from ASSET team - exploiting chemical kintetic models and computing Bayes factors to study how EWS-FLI1 employs an E2F switch to drive target gene expression - Nucleic Acids Research.
Bui, T. and Girolami, M. "Solving Large-Scale PDE-constrained Bayesian Inverse problems with Riemann Manifold Hamiltonian Monte Carlo", Inverse Problems, 30, 114014, doi:10.1088/0266-5611/30/11/114014.
Filiponne, M. and Girolami, M. "Pseudo-Marginal Bayesian Inference for Gaussian Processes", IEEE Transactions Pattern Analysis and Machine Intelligence, 36(11), 2214-2226, 2014.
Kramer A, Stathopoulos V, Girolami M, Radde N. MCMC_CLIB–an advanced MCMC sampling package for ODE models, Bioinformatics (2014) 30 (20): 2991-2992.
Book Chapter with Des Higham and Ben Calderhead on.... Zombies
Office No. D0.09
Department of Statistics
The University of Warwick
CV4 7AL, Coventry
Phone 44 (0)24 7657 4808
Fax 44 (0)24 7652 4532
Email address M dot Girolami at warwick dot ac dot uk