Peter Alonzi

Peter Alonzi is an Assistant Professor of Data Science at the University of Virginia's School of Data Science, appointed in 2022. He previously served as lead of research computing and held a postdoctoral position at the University of Washington. His research focuses on the intersection of mental health and criminal justice, with additional expertise in particle physics. Alonzi collaborates across disciplines, partnering with the School of Engineering, School of Medicine, and Darden School of Business on projects addressing societal challenges. He teaches courses like Data Wrangling in Python and Physics, and leads educational initiatives for the M.S. in Data Science program.

• Education: Ph.D. in Physics (University of Virginia), B.S. Physics (College of William and Mary, Magna Cum Laude)
• Labs: Paul Scherrer Institute, Fermilab, Oak Ridge National Laboratory, Jefferson Lab, TRIUMF
• Teaching Roles: Orientation leader, capstone project coach, curriculum committee co-chair

Alonzi's research explores criminal justice system inefficiencies, mental health service integration, and data-driven policy solutions. His work combines advanced computational methods with interdisciplinary collaboration. Recent projects analyze electronic incarceration efficacy, mental health screening in correctional facilities, and pandemic-era justice system adaptations.

His technical contributions include deep learning fraud detection models and particle physics instrumentation designs. Despite no explicitly listed awards, his collaborative approach and applied data science focus reflect sustained academic engagement.