Statistical methods for complex spatial, spatiotemporal and geometric data.
My research program sits at the intersection of Bayesian spatial and spatiotemporal statistics, Gaussian processes, differential geometry, and scalable statistical computing. My current and future work develops this program along three interconnected directions: differential inference for spatial and spatiotemporal processes; scalable Gaussian process methodology; and statistical inference over non-Euclidean domains and Riemannian manifolds. These methodological developments find applications in public health, environmental science, ecology, spatial omics, and biomedical science.
If you are interested to work with me, please email me with a brief explanation of your research interests and a CV.

Education
Ph.D. in Statistics
University of Connecticut
Storrs, Connecticut, USA
M.S. in Statistics
University of Connecticut
Storrs, Connecticut,USA
M.Sc. in Applied Mathematics
Chennai Mathematical Institute
Chennai, India
B.Sc. in Statistics
Presidency College, University of Calcutta
Kolkata, India

