Department of Pure Mathematics and Mathematical Statistics
We
investigate
the mathematical foundations and theory
of
inference problems arising in contemporary statistics and data
science with a particular focus on statistical
algorithms
in
non-convex, high- and infinite dimensional models, involving partial
differential equations (PDE), stochastic processes,
and
inverse problems. The mathematics involved lies at the intersection
of statistics, probability and analysis.
Currently
we are supported by
an
ERC
Advanced Grant
(2024-2029,
via UKRI) as well as an EPSRC
Programme Grant
(2022-2027).
From 2015-2021 we were supported by a Consolidator Grant of the European Research Council (ERC).
NEW: Conference for Vladimir Koltchinskii
NEW: Workshop in September 2024 in Cambridge
Research topics include:
statistics for PDEs, inverse problems & stochastic processes
Bayesian nonparametrics and computation
confidence regions for high-dimensional statistical models
concentration of measure and empirical process theory
Current group members:
Some former group members:
Randolf Altmeyer, Jan Bohr, Alexandra Carpentier, Matteo Giordano, Adam Kashlak, Hanne Kekkonen, Karim Lounici, Jakob Söhl, Kolyan Ray, Bharath Sriperumpudur Sven Wang
Some links:
Video lecture at ICM 2022
