Professor Mark Girolami
|Position||Chair in Statistics|
|Phone (external)||+44(0)20 7679 1861|
|Themes||Computational Statistics, Multivariate and High Dimensional Data, Biostatistics|
Mark Girolami is Professor of Statistics in the Department of Statistical Science. He also holds a professorial post in the Department of Computer Science at UCL and is Director of the Centre for Computational Statistics and Machine Learning (CSML), a large multi-faculty centre of world leading research excellence in statistical science, statistical learning theory, and statistical machine learning.
His research, and that of his group, addresses the theory, methodology and application of Computational Statistics and has very strong multidisciplinary interactions with the life, clinical, physical and engineering sciences. He has an H-index of 36 and currently holds a portfolio of research funding from EPSRC and BBSRC.
Prior to joining UCL Mark held a Chair in Computing and Inferential Science at the University of Glasgow. He is currently Editor-in-Chief of Statistics and Computing, an Associate Editor for J. R. Statist. Soc. C, Journal of Computational and Graphical Statistics and Area Editor for Pattern Recognition Letters. He is a member of the Research Section of the Royal Statistical Society.
In his copious spare time he enjoys cycling to exhaustion, fine dining in Michelin starred restaurants, enjoying the occasional Cuban cigar, and looking after his feline friends.
- 2012 - 2017. Royal Society Wolfson Research Merit Award
- 2012 - 2017. EPSRC Established Career Research Fellowship
- 2011. Elected as a Fellow of the Royal Society of Edinburgh (FRSE)
- 2009. Pioneer Award by the International Society of Optics and Photonics (SPIE)
- 2007 - 2012. EPSRC Advanced Research Fellowship
- 2007. Royal Academy of Engineering Senior Research Fellowship (declined)
- 2012 - 2016 - EPSRC - Research Network on Computational Statistics and Machine Learning - EP/K009788 (PI)
- 2012 - 2015 - EPSRC - Interactive Machine Learning Accelerating Progress in Science - EP/K015664 (PI)
- 2013 - 2018 - EPSRC - Established Career Fellowship - Advancing the Geometric Framework for Computational Statistics - EP/J016934 (PI)
- 2013 - 2017 - EPSRC - RCUK Centre for Energy Epidemiology - EP/K011839 (CI)
- 2011 - 2016 - EPSRC - Programme Grant - A Population Approach to Ubicomp Design - EP/J007617 (CI)
- Stathopoulos V. Girolami M. (2013) Markov chain Monte Carlo inference for Markov jump processes via the linear noise approximation. Phil. Trans. R. Soc. A, 371, 20110549.
- Diethe T. Girolami M. (2013) Online Learning with (Multiple) Kernels: A Review. Neural Computation, pp 1 - 59.
- Zhong M. Girolami M. (2012) A Bayesian Approach to Approximate Joint Diagonalisation of Square Matrices. ICML.
- Girolami M. Calderhead B. (2011) Riemann manifold Langevin and Hamiltonian Monte Carlo methods. J. R. Statist. Soc. B (with discussion). 73, Part 2. pp 1-37.
- Zhong M. Girolami M. Faulds K. Graham D. (2011) Bayesian methods to detect dye-labelled DNA oligonucleotides in multiplexed Raman spectra. J. R. Statist. Soc. C. 60, Part 3. pp 1-20.
- Xu T. Vyshemirsky V. Gormand A. von Kriegsheim A. Girolami M. Baillie G. Ketley D. Dunlop A. Milligan G. Houslay M. and Walter Kolch. (2010) Inferring Signaling Pathway Topologies from Multiple Perturbation Measurements of Specific Biochemical Species. Science. Signal. Volume 3, Issue 113. pp 1 - 10.
Page last modified on 13 jan 13 23:05