Professor Deligiannidis studied Mathematics (MMath) at the University of Warwick and Financial Mathematics (MSc) at Heriot-Watt University and the University of Edinburgh. After obtaining his PhD from the School of Mathematical Sciences of the University of Nottingham, he moved to the Department of Mathematics of the University of Leicester as a Teaching Assistant/Fellow. In 2012 […]
Dr. Mihai Cucuringu finished his PhD in Applied and Computational Mathematics (PACM) at Princeton University in June 2012, where he was advised by Prof Amit Singer. His thesis was on the low-rank matrix completion problem and several distance geometry problems with applications to sensor network localization and three-dimensional structuring of molecules. Dr. Cucuringu is a […]
Prof. Gesine Reinert is a University Lecturer at the Department of Statistics, Oxford, and Fellow at Keble College, Oxford (2000 – present). Her current and main research interests are in network statistics and to investigate such networks in a statistically rigorous fashion. Often this will require some approximation, and approximations in statistics are another of […]
Prof. Charlotte Deane’s group works in the protein bioinformatics area. Currently the research focuses on understanding protein structure and improving our ability to model and design proteins. To this end, the group is developing a rigorous definition of evolutionary relationships between proteins of differing structures using, in the initial stages, genomic data and building novel […]
Assoc. Prof. Dino Sejdinovic is broadly interested in statistical foundations underpinning large-scale machine learning algorithms, with a particular emphasis on nonparametric and kernel methods, and the resulting expressive models. Recent research focused on methods for discovery of higher-order interactions in datasets (when weak individual causes combine in a nonlinear way to form a strong effect), […]
Prof. Arnaud Doucet’s research concerns numerical methods for the analysis of complex data sets. In particular, he has contributed to the development and study of sequential Monte Carlo and Markov chain Monte Carlo methods.
Prof. Yee Whye Teh’s research interests are in machine learning and computational statistics, in particular scalable learning, probabilistic models, Bayesian nonparametrics and deep learning. He is particularly interested in theoretically well-founded, but practically relevant, statistical algorithms for learning from data. He has worked on applications in genetics/genomics, text processing, recommender systems, and machine vision.
Dr. Sarah Filippi joined the Department of Statistics of Oxford University in June 2014. She previously held a Medical Research Council Fellowship (2011-2104) in the Theoretical Systems Biology group at Imperial College London where she worked on a range of topics in computational statistics focused on understanding biological processes and their relation to disease. Prior […]
Prof. François Caron’s research interests lie in the development of statistical models and computational procedures for the analysis of structured data, with particular interest in Bayesian nonparametrics and Monte Carlo methods. His recent research focuses on building probabilistic models of network data which can capture the salient properties of real-world networks (sparsity, modularity), as well […]
I am Professor of Biostatistics at the University of Oxford with a joint appointment between the Department of Statistics and the Nuffield Department of Clinical Medicine through the Wellcome Trust Centre for Human Genetics. I hold a Programme Leader’s award in Statistical Genomics from the Medical Research Council UK. My research interests are in statistical […]