Portrait of Saumyadipta Pyne, PhD, Adjunct Professor at UCSB

Saumyadipta Pyne

Ph.D.

Adjunct (Full) Professor
Department of Statistics and Applied Probability
University of California Santa Barbara, CA 93106
Senior Research Fellow, National Institutes of Health (NIH)

Contact

Email: spyne@healthanalytics.net, spyne@ucsb.edu
URL:   https://www.pstat.ucsb.edu/people/continuing-lecturers/saumyadipta-pyne

About

Dr. Pyne's 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, dynamic and emergent phenomena, public and environmental health.

Intellectual Contributions

Pyne lab focuses on developing effective analytical solutions to problems arising in different domains - especially those complicated by dynamic observations and heterogeneous outcomes.

Dr. Pyne is known for his out-of-the-box innovative ideas and eclectic solutions that combine elements from applied mathematics, statistics, biology, physics, and AI/ML. His new applications lie in areas that overlap Data Fusion, Deep Learning, and Generative AI.

Recently, Dr. Pyne proposed a new computational framework for systematic reconstruction of trajectories (SRoT) to gain key insights into dynamic phenomena that cannot be observed sufficiently thoroughly for practical reasons.

Examples of such applications:

Through his writings and presentations to Data Science and AI task forces, Dr. Pyne provides strategic inputs for policies and standards such as for benchmarking different characteristics of data.

Background

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.

Dr. 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. In 2022, he was awarded the National Service Data Scholarship by NIH.

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

  1. Pyne S, Ray D, Ray MS. "Automated generation of personalized trajectories of aging phenotypes with DyViA-GAN". bioRxiv. 2025.08.22.671831, 2025.
  2. Ray S, Das Mandal S, Lall S, Pyne S. "Generative Reconstruction of Unobserved Cellular Dynamics using Single-Cell Transcriptomic Trajectories". bioRxiv. 2025.12.29.696948, 2025.
  3. Khademioureh S, Amini P, Ghasemi E, Calistrate-Petre P, Pyne S (co-senior author), Dinu I. "Stability and Performance of Linear Combination Tests of Gene Set Enrichment for Multiple Covariance Estimators in Unbalanced Studies". bioRxiv. 2025.01.23.634558, 2025.
  4. Ray D, Hajihosseini M, Pyne S. "Recent Advances in Deep Learning with Applications in Data Fusion and Agriculture", in Parsad R, Arora A. (ed.s), Harvesting Intelligence: The AI Revolution in Agriculture, Springer, 2025.
  5. Akhlaghi M, Ghasemi E, Ray M, Pyne S. "Predicting Clinical Phenotypes by Growth Curve Modeling of Transcriptomic Signatures during Disease Progression". Statistics and Applications, 2025.
  6. Nezarat F, Ghajar S, Khademioureh S, Pyne S (co-senior author), Dinu I. "On Potential Association of COVID-19 Infection during Pregnancy and Epigenetic Regulation of Metabolic Pathways in Newborns". International Journal of Medical Science and Health Research. 2025.
  7. Wigerblad G, Carruthers J, Ray S, Finnie T, Lythe G, Pyne S (co-senior author), Molina-Paris C, Kaplan MJ. "A mathematical framework for human neutrophil state transitions inferred from single-cell RNA sequence data". Frontiers in Immunology. 16:1654015, 2025. (Published Oct 24, 2025; Special Topic: Mathematical Modeling in Discovery and Analysis of Immune Responses)
  8. Wainwright B, Ghasemi E, Ali MH, Ray M, Pyne S (co-senior author), Jammalamadaka SR. "Circadian Gene Expression Analysis Using an Enhanced Circular Functional Framework". Sankhya B, 2025.
  9. Deo V, Gurewitsch R, Guha S, Ray M, Pyne S. "Analysis of Spatial and Temporal Patterns in Deaths of Despair in the Appalachian Region of the United States". Statistics and Applications, 22(3): 555-573, 2024.
  10. Guha S, Alonzo M, Goovaerts P, Brink L, Ray M, Bear T, Pyne S. "Disaggregation of green space access, walkability, and behavioral risk factor data for precise estimation of local population characteristics". International Journal of Environmental Research and Public Health, 21, 771, 2024.

Some Past Publications

  1. 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.
  2. 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.
  3. 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.
  4. Hajihosseini M, Amini P, Voicu D, Dinu I, Pyne S. Geostatistical Modeling and Heterogeneity Analysis of Tumor Molecular Landscape. Cancers, 14, 5235, 2022.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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").
  11. Ahfock D, Pyne S, McLachlan G. Data fusion using factor analysis and low-rank matrix completion. Statistics and Computing, 31:58, 2021.
  12. 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.
  13. 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.
  14. 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.
  15. Kedem B, Pyne S. Estimation of Tail Probabilities by Repeated Augmented Reality. Journal of Statistical Theory and Practice, 15:25, 1-16, 2021.