P1020600wGavino Puggioni

Formally:
UNC BMElab Postdoctoral Research Associate 10/01/2008 – 09/23/2009
Department of Environmental Sciences and Engineering
University of North Carolina at Chapel Hill
Chapel Hill, NC 27599-7431

Currently:
Postdoctoral Research Associate in the Center for Disease Ecology and in the Department of Biostatistics and Bioinformatics
Emory University
Wayne Rollins Research Center
1510 Clifton Rd. NE, Atlanta GA 30322
e-mail: gavino.puggioni@emory.edu

Education

  • Duke University, Ph.D. in Statistical Science (expected 2008)
  • Duke University, M.Sc. in Statistics and Decision Sciences (April, 2006)
  • Bocconi University, M.Sc. in Economics (June, 2003)
  • Bocconi University, B.Sc. in Economics (Mar, 2002)

Research Interests

  • Bayesian Statistics
  • Stochastic Differential Equations
  • Spatiotemporal Modeling and Mapping of Environmental Conditions
  • Environmental Exposure and Risk Assessment
  • Econometrics

Research Activities

  • Postdoctoral Research Associate, Environmental Sciences & Engineering, University of North Carolina at Chapel Hill, NC  (October 2008 – current).
  • PhD Student, Duke University, Durham:   Sept. 2003 – current.

Current Projects

  • Space-time Mapping of Air Pollutants in the United Arab Emirates (UAE).
  • Burden of Disease due to Exposure to Air Pollutant in the United Arab Emirates (UAE).

Publications

  • Puggioni G, Gelfand AE (2008). "Spatiotemporal modeling using Stochastic Differential Equations" (In preparation).
  • Puggioni G, Gelfand AE (2008). “Analyzing Space-time Sensor Network Data under Suppression and Failure in Transmission" (Submitted to Statistics and Computing).
  • Rodriguez A, Puggioni G (2008). “Bayesian Approaches to Mixed Frequency Data” (Submitted to International Journal of Forecasting).
  • Puggioni G, Gelfand AE, Miglioretti D, Elmore J (2008) "Joint Modeling of Sensitivity and Specificity", Statistics in Medicine, 27 (10), 1565-1800.
  • Silberstein A, Puggioni G, Gelfand A, Munagala K, Yang J (2007) "Making Sense of Suppressions and Failures in Sensor Data: A Bayesian Approach", VLDB 2007: 842-853.

 

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