Professor of Mathematical Statistics
Research Interests: Mathematical Statistics; specifically high-dimensional inference, Bayesian nonparametrics, statistics for PDEs and inverse problems, empirical process theory.
Publications
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 Poincaré, Probabilités et Statistiques
(2024)
60,
2619
(doi: 10.1214/23-aihp1397)
ON POSTERIOR CONSISTENCY OF DATA ASSIMILATION WITH GAUSSIAN PROCESS PRIORS: THE 2D-NAVIER–STOKES EQUATIONS
– Annals of Statistics
(2024)
52,
1825
(doi: 10.1214/24-AOS2427)
Consistent inference for diffusions from low frequency measurements
– Annals of Statistics
(2024)
52,
519
(doi: 10.1214/24-aos2357)
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions
– Philos Trans A Math Phys Eng Sci
(2023)
381,
20220150
(doi: 10.1098/rsta.2022.0150)
On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
– Journal of the European Mathematical Society
(2022)
26,
1031
(doi: 10.4171/JEMS/1304)
STATISTICAL GUARANTEES for BAYESIAN UNCERTAINTY QUANTIFICATION in NONLINEAR INVERSE PROBLEMS with GAUSSIAN PROCESS PRIORS
– Annals of Statistics
(2021)
49,
3255
(doi: 10.1214/21-aos2082)
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