Prof. Pyne directs 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.

He has been honored with oration awards, international fellowships, chair and visiting professorships, memorial and keynote lectures. He serves in the editorial boards of international journals including the Japanese Journal of Statistics and Data Science, and Statistics and Applications.
 

Some Recent Publications:

1. 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. 

2. 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. 

3. 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. 

4. 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. 

5. 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".) 

6. Ahfock D, Pyne S, McLachlan G. Data fusion using factor analysis and low-rank matrix completion. Statistics and Computing, 31:58, 2021. 

7. 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.  

8. 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.  

9. 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. 

10. Kedem B, Pyne S. Estimation of Tail Probabilities by Repeated Augmented Reality. Journal of Statistical Theory and Practice. 15:25, 1-16, 2021.