Summary
Loreto Alonzi is an Assistant Professor of Data Science and former lead of research computing at the University of Virginia, combining over a decade of experience in particle physics and applied data science. He holds a PhD in Physics and has translated deep experimental-lab expertise—from Fermilab to Paul Scherrer Institute—into practical computational research, teaching, and program leadership. Loreto’s research bridges datalogy and the intersection of mental health and the criminal justice system, reflecting a rare blend of quantitative rigor and social-impact focus. He designs and teaches hands-on technical boot camps, mentors capstone projects, and co-chairs the undergraduate curriculum, shaping both pedagogy and practice within the School of Data Science. Prior roles include a postdoc at the University of Washington where his simulation work directly informed funded instrument design, highlighting his track record of turning complex simulations into real-world outcomes. Based in Charlottesville, he pairs strong collaborative ties across engineering, medicine, and business with an active publication and researcher profile (ORCID and Google Scholar).
11 years of coding experience
15 years of employment as a software developer
Bachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at The College of William and Mary
Doctor of Philosophy (PhD), Physics, Doctor of Philosophy (PhD), Physics at University of Virginia