Ferdinando (Nando) Fioretto

Ferdinando (Nando) Fioretto is an assistant professor of Computer Science at the University of Virginia. His research focuses on addressing foundational challenges to advance artificial intelligence, privacy, fairness, and the intersection between machine learning and optimization.

In particular, his group focuses on two key questions: (1) How to endow discriminative and generative ML models the ability to comply with constraints, uphold physical principles, and adhere to safety standards, and (2) How to ensure that ML models and decision making systems adhere to safety, privacy, and fairness principles. While the focus of his research is foundational, Nando’s research is motivated by the application of ML in science and engineering, with applications to power systems, material science, policy optimization, and beyond.

His work has been recognized with the 2022 Caspar Bowden PET award, the IJCAI-22 Early Career spotlight, the 2017 AI*AI Best AI dissertation award, and several best paper awards. Nando is also a recipient of the NSF CAREER award, the Google Research Scholar Award, the Amazon Research Award, the ISSNAF Mario Gerla Young Investigator Award, and the ACP Early Career Researcher Award in Constraint Programming. He is a board member of the Artificial Intelligence Journal (AIJ) and has been a member of the organizing committee of several workshops, tutorials, and events with focus on privacy, fairness, and optimization at premier AI and ML venues.

He holds a dual PhD degree in Computer Science from the University of Udine and the New Mexico State Universty. Before joining the University of Virginia, Nando was an assistant professor at Syracuse University, a postdoctoral research associate at the Georgia Institute of Technology and a research fellow at the University of Michigan.