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Peter Alonzi Recognized with 2026 Breakthrough Prize in Fundamental Physics
The University of Virginia School of Data Science celebrates a major international honor recognizing the contributions of Peter Alonzi, assistant professor of data science, as part of a global scientific collaboration that received the 2026 Breakthrough Prize in Fundamental Physics.
The prize was awarded to the Muon g-2 collaborations at CERN, Brookhaven National Laboratory, and Fermilab for their groundbreaking work measuring the anomalous magnetic moment of the muon, a fundamental particle that offers insight into the laws governing the universe. The collaboration’s precise measurements test the limits of the Standard Model of particle physics and open new pathways for discovering previously unknown physics, placing the work at the forefront of the field’s “precision frontier.”
The Breakthrough Prize, often referred to as the “Oscars of Science,” honors transformative advances in fundamental physics, life sciences, and mathematics. The Muon g-2 collaboration’s achievement stands as one of the most precise tests of particle physics to date, with implications for how scientists understand the structure and behavior of the universe at its most fundamental level.
Alonzi is among the named contributors to the award-winning effort, which represents decades of international collaboration across institutions and disciplines. His work reflects the increasingly central role of advanced data analysis, statistical modeling, and computational methods in modern physics — areas where data science and fundamental science intersect.
“I’m honored to be part of this collaboration," Alonzi said. "It reflects a true team effort, and I’m grateful the committee recognized that spirit. It also speaks to what drew me to UVA Data Science, a commitment to data science as a team sport.”
Alonzi’s research sits at the intersection of particle physics and data science, with a focus on developing advanced statistical methods to analyze large-scale experimental data. He has worked extensively on high-energy physics experiments, including the Muon g-2 project, applying techniques in uncertainty quantification, signal extraction, and precision measurement. Before joining the School of Data Science, Alonzi trained as a physicist, contributing to major international collaborations and bringing deep expertise in both theoretical frameworks and computational approaches to complex scientific questions.
“This recognition underscores the power of collaboration at scale and the critical role data science plays in advancing discovery,” said Stephen Turner, assistant dean for research at the School of Data Science.
At the School of Data Science, Alonzi’s research and teaching contribute to a growing portfolio of work at the intersection of physics, computation, and data-driven discovery, advancing the School’s mission to practice and teach responsible data science for the common good.
