Thomas Cass is a Reader at the Mathematics Department at Imperial College London and a Visiting Researcher at the Alan Turing Institute in London. He completed his MA and PhD at the University of Cambridge, and he has previously held positions at the University of Oxford. His research interests span a number of areas of pure and applied mathematics; he has written fundamental research papers in the areas of probability and stochastic analysis as well as in mathematical finance. Much of his research uses the theory of rough paths and rough analysis, which has rapidly become a major tool in mathematics over the past two decades. Its applications can now be across multiple research areas, including probability and analysis, mathematical finance and, mostly recently, in data science.
RESEARCH projects and Leadership Roles
Thomas is involved in major long-term projects funded by the UK Research and Innovation (UKRI). He is a Co-Investigator on the EPSRC Programme Grant EP/S026347/1, Unparameterised multi-modal data, high order signatures, and the mathematics of data science (DataSig).
This five-year project (2019-2024) will embed rough path analysis as a core tool in the data science of multimodal unparameterized streams, and will develop broad computational tools derived from four challenge areas: computer vision, radioastronomy, human-computer interaction and mental health. More details on the DataSig project and its activities and outputs can be found on the DataSig website.
Thomas is a Co-Director, and Imperial College lead, for the EPSRC Centre for Doctoral Training (CDT) in the Mathematics of Random Systems: Analysis, Modelling and Simulation, a collaboration between Imperial College and the University of Oxford.
The CDT is training the next generation of inter-disciplinary researchers across a spectrum of research areas in stochastic analysis, modelling and data science. Information on the CDT, its activities, industry sponsors and the current student cohorts can be found on the CDT's website.
Cass T, Lim N, Skorohod and rough integration for stochastic differential equations driven by Volterra processes, l' Institut Henri Poincare. Annales (B). Probabilites et Statistiques, ISSN:0246-0203
et al., 2020, Mean field games with parametrized followers, IEEE Transactions on Automatic Control, Vol:65, ISSN:0018-9286, Pages:12-27
Cass T, Lim N, 2019, A Stratonovich-Skorohod integral formula for Gaussian rough paths, Annals of Probability, Vol:47, ISSN:0091-1798, Pages:1-60
Cass T, Ogrodnik M, 2017, Tail estimates for Markovian rough paths, Annals of Probability, Vol:45, ISSN:0091-1798, Pages:2477-2504
et al., 2016, On the integration of weakly geometric rough paths, Journal of the Mathematical Society of Japan, Vol:68, ISSN:0025-5645, Pages:1505-1524
Cass T, Driver BK, Litterer C, 2015, Constrained Rough Paths, Proceedings of the London Mathematical Society, Vol:111, ISSN:1460-244X, Pages:1471-1518
Cass T, Lyons T, 2015, Evolving communities with individual preferences, Proceedings of the London Mathematical Society, Vol:110, ISSN:0024-6115, Pages:83-107
Cass T, Litterer C, Lyons T, 2013, Integrability and tail estimates for Gaussian rough differential equations, Annals of Probability, Vol:41, Pages:3026-3050
et al., 2012, Smoothness of the density for solutions to Gaussian Rough Differential Equations
Cass T, 2009, Smooth densities for solutions to stochastic differential equations with jumps, Stochastic Processes and Their Applications, Vol:119
Cass T, Friz P, Victoir N, 2009, Non-degeneracy of Wiener functionals arising from rough differential equations, Transactions of the American Mathematical Society, Pages:3359-3371