Email:
spyne@healthanalytics.net, spyne@ucsb.edu

URL:
https://www.pstat.ucsb.edu/people/saumyadipta-pyne

About:

Prof. Pyne advises HEED-lab of Health Analytics Network, which conducts interdisciplinary research with the unique vision of achieving Health and Environmental Equity through Data.

His areas of research include computational statistics, machine learning, data fusion and disaggregation, models of population heterogeneity, spatial complexity, skew and mixture distributions, high-dimensional and big data analysis with applications in biomedical informatics, biostatistics, detection and prediction of rare events, emergent phenomena, public health and environmental disparities.

Over the past decades, he has led and participated in many international collaborations, consortia and capacity-building projects. He has long-standing collaborations with researchers in several countries including Australia, Canada, India, the UK, etc.

Prof. Pyne has been honored with oration awards, international fellowships, chair and visiting professorships, public felicitation, memorial and keynote lectures. These include Ramalingaswami Fellowship of the Department of Biotechnology, India; and Senior Research Fellowship of the NIH, USA.

He served as the PC Mahalanobis Chair Professor and Head of Bioinformatics at the CR Rao Advanced Institute of Mathematics, Statistics and Computer Science. Formerly, he was the Scientific Director of the Public Health Dynamics Lab at the University of Pittsburgh.

He serves in the editorial boards of multiple journals including the International Journal of Environmental Research and Public Health, Japanese Journal of Statistics and Data Science, and Statistics and Applications.

Some Recent Publications:

Guha S, Petersen A, Ray S, Pyne S. On Rao’s Weighted Distributions for Modeling the Dynamics of Wildfires and Air Pollution. Proceedings of Applied Linear Algebra, Probability and Statistics, Springer (in press). 2022.
Pyne S, Guha S, Das S, Ray M, Chandra H. Food Insecurity in the Eastern Indo-Gangetic Plain: Taking a Closer Look. PLOS ONE (in press). 2022.
Stacy S, Chandra H, Guha S, Gurewitsch R, Brink L, Robertson L, Wilson D, Yuan J-M, Pyne S. Rescaling and Small Area Estimation of Behavioral Risk Survey guided by Social Vulnerability Data. BMC Public Health (in press). 2022.
Hajihosseini M, Amini P, Voicu D, Dinu I, Pyne S. Geostatistical Modeling and Heterogeneity Analysis of Tumor Molecular Landscape. Cancers, 14, 5235, 2022.
Ray S, Desai M, Pyne S. Systematic mining of patterns of polysubstance use in a nationwide population survey. Computers in Biology and Medicine, 151(A), 106175, 2022.
Ahfock D, Pyne S, McLachlan G. Statistical file matching of non-Gaussian data: A Game Theoretic Approach. Computational Statistics and Data Analysis, 168, 107387, 2022.
Ali MH, Wainwright B, Petersen A, Jonnadula GB, Aruru M, Rao HL, Srinivas MB, Rao JS, Senthil S, Pyne S. Circular functional analysis of OCT data for precise identification of structural phenotypes in the eye. Scientific Reports, 11, 23336, 2021.
Fox G, Lasewski G, Wang F, Pyne S. AICov: An Integrative Deep Learning Framework for COVID-19 Forecasting with Population Covariates. Journal of Data Science, 19(2):293-313, 2021.
Kedem B, Stauffer R, Zhang X, Pyne S. On the Probabilities of Environmental Extremes. International Journal of Statistics in Medical Research, 10, 72-84, 2021.
Zhang X, Pyne S, Kedem B. Multivariate Tail Probabilities: Predicting Regional Pertussis Cases in Washington State. Entropy, 23, 675, 2021. (Special Issue on "Modeling and Forecasting of Rare and Extreme Events").
Ahfock D, Pyne S, McLachlan G. Data fusion using factor analysis and low-rank matrix completion. Statistics and Computing, 31:58, 2021.
Nielsen F, Marti G, Ray S, Pyne S. Clustering Patterns connecting COVID-19 Dynamics and Human Mobility using Optimal Transport. Sankhya B, 83:167-184, 2021.
Gharani P, Ray S, Aruru M, Pyne S. Differential patterns of social media use associated with loneliness and health outcomes in selected socioeconomic groups. Journal of Technology in Behavioral Science, 6, 535–544, 2021.
Dinu I, Khodayari Moez E, Hajihosseini H, Leite AP, Pyne S. Use of Linear Combination Test to Identify Gene Signatures of Human Embryonic Development in Single Cell RNA-Seq Experiments. Statistics and Applications, 19(1):431-442, 2021.
Kedem B, Pyne S. Estimation of Tail Probabilities by Repeated Augmented Reality. Journal of Statistical Theory and Practice, 15:25, 1-16, 2021.