Professor of Mathematical Statistics
Research Interests: Mathematical Statistics; specifically high-dimensional inference, Bayesian nonparametrics, statistics for PDEs and inverse problems, empirical process theory.
Publications
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
– pp
(2019)
3,
385
(doi: 10.1007/978-3-030-26391-1_18)
Efficient nonparametric Bayesian inference for $X$-ray transforms
– Annals of Statistics
(2019)
47,
1113
(doi: 10.1214/18-AOS1708)
Bernstein-von Mises theorems for statistical inverse problems II: compound Poisson processes
– Electronic Journal of Statistics
(2019)
13,
3513
(doi: 10.1214/19-EJS1609)
Uncertainty Quantification for Matrix Compressed Sensing and Quantum Tomography Problems
(2019)
74,
385
(doi: 10.1007/978-3-030-26391-1_18)
Adaptive confidence sets for matrix completion.
– Bernoulli
(2018)
24,
2429
(doi: 10.3150/17-BEJ933)
Inference on covariance operators via concentration inequalities: K-sample tests, classification, and clustering via rademacher complexities
– Sankhya A
(2018)
81A,
214
(doi: 10.1007/s13171-018-0143-9)
Comments on: High-dimensional simultaneous inference with the bootstrap
– Test
(2017)
26,
731
(doi: 10.1007/s11749-017-0558-y)
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