Assistant Professor of Biostatistics
Epidemiology and Biostatistics
ah3758@drexel.edu
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Degrees

PhD, Statistics, University of Connecticut
MS, Statistics, University of Connecticut
MS, Applied Mathematics, Chennai Mathematical Institute
BS, Statistics, Presidency College

Bio

Aritra Halder is an assistant professor of Biostatistics in the Department of Epidemiology and Biostatistics, at the Dornsife School of Public Health, Drexel University. He completed his PhD in Statistics from the University of Connecticut in July, 2020.

His research program sits at the intersection of Bayesian spatial and spatiotemporal statistics, Gaussian processes, differential geometry, and scalable statistical computing. His 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.

Research Interests

• Bayesian Modeling
• Spatiotemporal Statistics
• Spatial Statistics

Publications

Halder, A., Li, D. and Banerjee, S. (in press, 2024+) Bayesian Spatiotemporal Wombling, Journal of the American Statistical Association, Theory & Methods. PMC13664449 https://doi.org/10.1080/01621459.2026.2700798

Halder, A. and Banerjee, S. (in press, 2025+) nimblewomble: An R package for Bayesian Wombling using nimble, R-Journal https://doi.org/10.32614/RJ-2026-026

Chen, J., Xiong, C., Sun, Q., Wang, G. W., Gupta, G. P., Halder, A., Li, Y. and Li, D. (2024+) Investigating spatial dynamics in spatial omics data with StarTrail, Journal of the American Statistical Association, Applications & Case Studies. PMC1346541 https://doi.org/10.1080/01621459.2026.2700798

Halder, A., Banerjee, S. and Dey, D. K. Bayesian Modeling with Spatial Curvature Processes. (2023) 119(546), pp. 1155–1167, Journal of the American Statistical Association, Theory & Methods. PMC11238907 https://doi.org/10.1080/01621459.2023.2177166

Mukherjee, R., Halder, A., Naik, S., Sansare, S. and Chaudhuri, B. (2020). A Simplex Centroid Design to quantify triboelectric charging in pharmaceutical mixtures. Journal of Pharmaceutical Sciences, Elsevier.

Yang, C. and Halder, A. (2019). Categorical perception of Mandarin tones by native and second language (L2) speakers. In Proceedings of the 30th North American Conference on Chinese Linguistics, Columbus, Ohio. The Ohio State University.

Ray, D., Salvatore, M., Bhattacharyya, R., Wang, L., Du, J., Mohammed, S., Purkayastha, S., Halder, A., Rix, A., Barker, D., Kleinsasser, M., Zhou, Y., Bose, D., Song, P., Banerjee, M., Baladandayuthapani, V., Ghosh, P., Mukherjee, B. (2020) Predictions, role of interventions and effects of a historic national lockdown in India’s response to the COVID-19 pandemic: Data science call to arms.

Halder, A., Mohammed, S., Chen, K. and Dey, D.K. Spatial Tweedie exponential dispersion models. Scandinavian Actuarial Journal https://doi.org/10.1080/03461238.2021.1921017.

Das, S., Halder, A. & Dey, D.K. (2017). Regularizing Portfolio Risk Analysis: A Bayesian Approach, Methodology and Computing in Applied Probability. 19(3) 865 -- 889.

See Dr. Halder's complete list of publications on Google Scholar