Dr. Szpiro is Professor of Biostatistics at the University of Washington, where he has been a faculty member  2009 and was a post-doc from 2006 to 2009.  He was the founding Program Director of the MS Capstone program in the Department of Biostatistics starting in 2019.

Dr. Szpiro is an internationally recognized expert with 18+ years of experience leading methodological and collaborative research in statistical methods for environmental health. He is a core investigator of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) and the lead statistician for the Environmental Influences on Child Health Outcomes (ECHO) PATHWAYS, AWARE, and MEND projects and The Infant Development and Environment (TIDES III) study. He has investigated the association between exposure to air pollution and multiple clinical and subclinical health endpoints in MESA Air, ECHO, NIEHS Sisters Study, Hispanic Community Health Study / Study of Latinos (HCHS/SOL),  Pregnancy Study Online (PRESTO), Health and Retirement Study (HRS), Adult Changes in Thought (ACT), Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS),  and a national consortium of air pollution cohorts including electronic health records. 

Dr. Szpiro's methodological research in environmental Biostatistics includes spatio-temporal exposure modeling, measurement error correction, optimal exposure prediction modeling for health effect inference, dimension reduction for spatially misaligned data, machine learning for spatial data, analysis of mixtures of environmental exposures, and control for unmeasured spatial and/or temporal confounding.  A common conceptual theme is the role of random effects models in analyzing spatially or temporally structured data, in particular the importance of precisely characterizing sources of randomness/correlation in scientifically plausible data-generating mechanisms (as termed by Jim Hodges, "old-" vs "new-" style random effects).  

Dr. Szpiro has 10+ years of experience designing and analyzing randomized trials aimed at improving infectious disease prevention and care with novel differentiated service delivery (DSD) strategies for screening, linkage, and distribution of treatment. He is the protocol statistician for the Gates Foundation funded DO ART trial, which demonstrated improved outcomes with community-based ART initiation, delivery, and monitoring in people living with HIV. He is also the protocol statistician for the NIH/NIMH funded Deliver Health, Lotto-to-Link, and Smart ART trials that build on the success of DO ART by incorporating additional strategies for DSD at the individual and group level and the DO PrEP trial focused on pre-exposure prophylaxis. Dr. Szpiro is the protocol statistician for the ISBAAR trial of efficacy of self-sampling for HPV screening.

Dr. Szpiro is a core investigator and lead statistician for the national Interventions Supporting Physical ACtivity modified by the Environment (InSPACE) consortium of physical activity trials investigating the role of the built-environment in efficacy of physical activity interventions. Other notable ongoing and completed research projects include genetic epidemiology in HCHS/SOL and the Trans-Omics for Precision Medicine (TOPMed) project, the The Duwamish Air Improvement Study for Youth (DAISY), and studies of the health effects of greenness in HCHS/SOL and the Northern Manhattan Study (NOMAS).

Prior to coming to Seattle, Dr. Szpiro engaged in mathematical modeling and scientific consulting on national security issues (primarily air vehicle countermeasures and bioterrorism defense) at MIT Lincoln Laboratory between 1999 and 2006.  Dr. Szpiro received a Ph.D. and Sc.M. in Applied Mathematics from Brown University in 1999 and 1994, respectively, where he wrote his dissertation under the direction of Paul Dupuis on stochastic process based second-order numerical methods for Hamilton-Jacobi PDEs.  He received a B.A. (Summa Cum Laude) in Mathematics from Revelle College at UC San Diego in 1993.  During his undergraduate years, he had the opportunity to spend a few months tucked away at Oak Ridge National Laboratory proving interesting but almost certainly useless theorems about optimal saddle points for controlling biological systems.