Professor of Mathematical Statistics
Research Interests: Mathematical Statistics; specifically high-dimensional inference, Bayesian nonparametrics, statistics for PDEs and inverse problems, empirical process theory.
Publications
DATA ASSIMILATION WITH THE 2D NAVIER-STOKES EQUATIONS: OPTIMAL GAUSSIAN ASYMPTOTICS FOR THE POSTERIOR MEASURE
– The Annals of Statistics
(2026)
54,
2352
(doi: 10.1214/26-AOS2645)
Inferring diffusivity from killed diffusion
– The Annals of Statistics
(2026)
54,
2234
(doi: 10.1214/26-aos2633)
Inferring diffusivity from killed diffusion
– Annals of Statistics
(2026)
On gradient stability in nonlinear PDE models and inference in interacting particle systems
– arxiv preprint
(2026)
(doi: 10.48550/arXiv.2601.10326)
On low frequency inference for diffusions without the hot spots conjecture
– Mathematical Statistics and Learning
(2025)
8,
305
(doi: 10.4171/MSL/53)
Bayesian nonparametric inference in McKean–Vlasov models
– The Annals of Statistics
(2025)
53,
170
(doi: 10.1214/24-AOS2459)
On log-concave approximations of high-dimensional posterior measures and stability properties in non-linear inverse problems
– Annales De L Institut Henri Poincare B Probability and Statistics
(2024)
60,
2619
(doi: 10.1214/23-AIHP1397)
ON POSTERIOR CONSISTENCY OF DATA ASSIMILATION WITH GAUSSIAN PROCESS PRIORS: THE 2D-NAVIER–STOKES EQUATIONS
– The Annals of Statistics
(2024)
52,
1825
(doi: 10.1214/24-aos2427)
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