Team

girolami2.jpg Mark Girolami (PI) is a professor at Imperial College. He is an EPSRC Established Career Research Fellow (2012-2018) and was an EPSRC Advanced Research Fellow (2007-2012). He is the Director of the £10M Lloyds Register Foundation-Turing Programme on Data Centric Engineering and previously led the EPSRC funded Research Network on Computational Statistics and Machine Learning. In 2011 he was elected to the Fellowship of the Royal Society of Edinburgh when he was also awarded a Royal Society Wolfson Research Merit Award.

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Mike Giles is a Professor of Scientific Computing at the University of Oxford. His research focuses on improving the accuracy, efficiency and analysis of Monte Carlo methods. A particular highlight has been the development and numerical analysis of multilevel Monte Carlo methods which are now being used widely. He is interested in high performance parallel computing, and for almost 10 years has been working on the exploitation of GPUs (graphics processors) for a variety of financial, scientific and engineering applications. His research in ICONIC will cover both of these aspects, looking at the development and analysis of efficient Monte Carlo solution methods for the models developed by Mark and Des, and also the parallel computing implementation of the numerical methods on GPUs and other many-core processors such as Intel’s Xeon Phi.

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Des Higham is the 1966 Chair of Numerical Analysis at the University of Strathclyde. He is an EPSRC/RCUK Digital Economy Established Career Fellow. Des is a Fellow of the Royal Society of Edinburgh, a SIAM Fellow, and recently held a Royal Society Wolfson Research Merit Award. Des has experience in stochastic modelling and computation, and has been involved in extending the scope of Mike’s multilevel Monte Carlo techniques to discrete space models. He will be working with Mark on modelling and inference for urban behaviour, notably crime, and with Nick on some of the underlying issues in matrix computation.

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Nick Higham is Richardson Professor of Applied Mathematics at the University of Manchester. His research focuses on the development of algorithms, primarily in numerical linear algebra, and analysis of their accuracy and stability. In ICONIC his research topics will include functions of matrices, rounding error analysis, and matrix nearness and completion problems. In particular, he will work with Mike to develop effective mixed precision algorithms that exploit GPUs other many-core processors. Nick is a Fellow of the Royal Society, a SIAM Fellow, and a Member of Academia Europaea. He publishes a blog about applied mathematics.

Research Associates

Pierre Blanchard (University of Manchester) obtained his PhD in Applied Mathematics and Scientific Computing from the University of Bordeaux, France, in 2017. A theme of his research to date has been hierachical representation of matrices, as applied to various domains of scientific computing, including seismic wave scattering, materials sciences and geostatistics.

Theo Mary (University of Manchester) obtained his PhD in Applied Mathematics and Computer Science from the University of Toulouse, France, in 2017. His research to date has focused on exploiting low-rank approximations inside direct, factorization-based methods to reduce the computational cost of the solution of sparse linear systems arising in several applications, including seismic imaging, electromagnetic modeling, and structural mechanics.

Seppo Virtanen (Imperial College London) works at the intersection between statistical inference and mathematical modeling. His research interests include multi-view learning, latent variable modeling and approximate Bayesian inference.  His recent work focuses on dynamic models of text documents.

Research Assistants

Louis Ellam (Imperial College London) is a research assistant working on stochastic modelling and statistical inference for urban systems and is completing his PhD in Statistics at Imperial College London.  His research to date has focused on the development of new Bayesian methodologies for inverse problems, and has included high-dimensional Gaussian models, elliptic PDEs and singly-constrained dynamic urban models.

Associated Research Students

Jan Povala (Imperial College London) is a DPhil student working on crime prediction and statistical inference using spatio-temporal log-Gaussian Cox processes.  His project is part of the Financial Computing CDT at Imperial College London.

Oliver Sheridan-Methven (University of Oxford) is a DPhil student working on the use of high performance low/mixed precision vectorised computer arithmetic for stochastic simulations.  His project is sponsored by ARM and NAG and is part of the InFoMM CDT.