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Prithwish Ghosh

PhD Student in Statistics, North Carolina State University (Raleigh, NC)

About

I am a Ph.D. student in the Department of Statistics at North Carolina State University, working under the supervision of Dr. Sujit K. Ghosh. My research lies at the intersection of Bayesian computation, stochastic modeling, and data-driven scientific discovery, with a particular emphasis on methodological innovation and interdisciplinary applications. My primary research focus is on the development of novel, automated Markov chain Monte Carlo (MCMC) methods for inference from complex, high-dimensional, and non-standard probability models. In particular, I am developing scalable and theoretically grounded sampling algorithms that adapt to multimodal, heavy-tailed, and irregular target distributions without requiring manual tuning. This work aims to advance automated Bayesian inference for challenging real-world scientific problems. I am also deeply interested in spatio-temporal modeling and statistical learning for structured data. My work includes Bayesian classification and modeling frameworks for dependent data, directional statistics for spherical and manifold-valued observations, and uncertainty quantification techniques that ensure reliable scientific inference. A major application area of my research is astrostatistics. I work on statistical modeling of astronomical data, including spectral light curves, high-dimensional observational measurements, and directional phenomena arising in astrophysics. My recent projects involve integrating advanced computational methods—such as wavelet-based functional data analysis and modern generative modeling approaches—with principled Bayesian inference to analyze complex astronomical signals. Broadly, my research goal is to build theoretically sound, computationally efficient, and fully automated statistical methodologies that bridge modern Bayesian computation with large-scale scientific data, particularly in astronomy and related domains.

Education

Awards & Honors

Curriculum vitae