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 posterior consistency of data assimilation with Gaussian process
priors: the 2D Navier-Stokes equations
(2023)
On free energy barriers in Gaussian priors and failure of cold start MCMC for high-dimensional unimodal distributions.
– Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
(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)
On some information-theoretic aspects of non-linear statistical inverse
problems
(2021)
On log-concave approximations of high-dimensional posterior measures and
stability properties in non-linear inverse problems
(2021)
Consistent Inversion of Noisy Non-Abelian X-Ray Transforms
– Communications on Pure and Applied Mathematics
(2020)
74,
1045
(doi: 10.1002/cpa.21942)
Consistency of Bayesian inference with Gaussian process priors in an elliptic inverse problem
– Inverse Problems
(2020)
36,
085001
(doi: 10.1088/1361-6420/ab7d2a)
On statistical Calderón problems
– Mathematical Statistics and Learning
(2020)
2,
165
(doi: 10.4171/msl/14)
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