Gavino Puggioni

  • Associate Professor | Chair
  • Statistics
  • Phone: 401.874.4388
  • Email:
  • Office Location: Tyler Hall 254


I was born and raised in Italy, where I completed my undergraduate and masters studies in Economics at Bocconi University. My interest in statistics lead me to pursue a masters and a doctoral degree from Duke University. After graduation in 2008, I worked as a post-doctoral fellow at the University of North Carolina, Chapel Hill and at Emory University. I joined the Department of Computer Science and Statistics at the University of Rhode Island as an Assistant Professor in 2012 with a joint appointment at the College of the Environment and Life Sciences. I was promoted to my current rank of Associate Professor with tenure in 2018. Since 2017 I also have been serving as Statistics Section Head and as Graduate Director.


My main areas of research relate to the development and applications of Bayesian methods. I am particularly interested in the analysis of dependent data (time series, spatial, and spatio-temporal), stochastic differential equations, mixtures, and model averaging. I collaborate with scientists of different areas: ecology and environmental sciences, biology, oceanography, medicine, psychiatry, pharmacy, epidemiology, economics and finance.
My research has been funded by NASA, NIH, USDA and USAID. For more details, see my CV


Duke University
Durham, NC
Bocconi University
Milan, Italy


Selected Publications

Below are some of my most recent publications (2019-Present). For a complete list, see my CV

  1. Wang S, Puggioni G, Wen X (2022), “Bayesian Latent Class Model for Predicting Gestational Age in an Automated Database”. Published online in Pharmaceutical Statistics. doi
  2. Strock J, Puggioni G, Menden-Deuer S (2022), “Two Stage Multivariate Dynamic Linear Models to Extract Environmental and Climate Signals in Coastal Ecosystem Data“. Forthcoming in Statistics and its Interface
  3. Yang S, Puggioni G (2021) “A Bayesian Zero-inflated Latent Class Growth Model for Adolescent Health Risk Behaviors”, Statistics and its Interface, Vol. 14, No. 2, 151-163. doi
  4. Sudhakaran PO, Puggioni G, Uchida H, Opaluch J (2021) “Effect of Oyster Farms on Housing Prices in Rhode Island”. Published online in Aquaculture Economics and Management. doi
  5. Dyer M, Requintina M, Berger K, Puggioni G, Mather T (2021) “Evaluating the effect of minimal risk natural products for control of the tick, Ixodes scapularis (Acari: Ixodidae)”, Journal of Medical Entomology, Volume 58, Issue 1, 390–397 doi
  6. Langan J, Puggioni G, Oviatt C, Henderson E, Collie J (2021) “Climate Alters the Migration Phenology of Coastal Marine Species”. Forthcoming as Cover Feature Article in Marine Ecology Progress Series. doi
  7. Puggioni G, Couret N, Serman E, Akanda A, Ginsberg H (2020) “Spatiotemporal risk of Dengue Fever in Puerto Rico”, Spatial and Spatio-Temporal Epidemiology, Volume 35. doi
  8. Wibisono E, Puggioni G, Firmana E, Humphries A (2020) “Identifying hotspots for spatial management of the Indonesian deep-slope demersal fishery”. Accepted for publication. Conservation Science and Practice, doi
  9. Hayes R, Puggioni G, Parker W, Tiley C, Bednarick A, Fastovsky D (2020) “Modeling the dynamics of a Late Triassic vertebrate extinction: The Adamanian/Revueltian faunal turnover, Petried Forest National Park, Arizona, USA”, Geology, 48 (4): 318–322. doi
  10. Boussidi B, Cornillon P, Puggioni G, Gentemann G (2019) “Determining the AMSR-E SST Footprint from Co-located MODIS SSTs”, Remote Sensing, 11, 715; doi
  11. Spinette RF, Brown SM, Ehrlich A, Puggioni G, Deacutis C, Jenkins BD (2019) “Diazotrophic Activity in Narragansett Bay Sediments Measured during the Summer of 2013 and 2014: Effects of Dissolved Oxygen and Organic Matter”, Marine Ecology Progress Series, Vol. 614: 35-50; doi
  12. Sheinkopf S, Levine T, McCormick C, Puggioni G, Conradt E, Lagasse L, Lester B (2019) “Developmental Trajectories of Autonomic Functioning in Autism from Birth to Early Childhood”, Biological Psychology, 142:13-18. doi

Courses Taught

  • STA592 – Advanced Bayesian Statistics (S-2017, S-2019, F-2021)
  • STA560 – Time Series Analysis (F-2014, F-2016, S-2019)
  • STA545 – Bayesian Statistics (S-2013, S-2015)
  • STA550 – Ecological Statistics (F-2013, F-2014, F-2015, F-2016, F-2017, S-2019, F-2019, F-2020, F-2021)
  • STA515 – Spatial Data Analysis (S-2014, S-2016, S-2018, S-2021)
  • STA460 – Introduction to Time Series Analysis (F-2017)
  • STA409 – Statistical Methods in Research I (F-2012, S-2013)
  • STA308 – Introductory Statistics (S-2018, Smr-2017, Smr-2018)