Pietro Perona received a Ph.D. in electrical engineering and computer science from the University of California, Berkeley, in 1990. In 1990, he was postdoctoral fellow at the International Computer Science Institute at Berkeley. From 1990 to 1991, he was a postdoctoral fellow at the Massachusetts Institute of Technology in the Laboratory for Information and Decision Systems. In the fall of 1991, Perona joined the California Institute of Technology as assistant professor. He became full professor in 1996 and the Allen E. Puckett Professor of Electrical Engineering and Computation and Neural Systems in 2006. From 1999 to 2005, Perona was the director of the National Science Foundation Center for Neuromorphic Systems Engineering. Since 2005, he has led the Computation and Neural Systems program at the California Institute of Technology.
Perona’s research focuses on the computational aspects of vision and learning. He is known for the anisotropic diffusion equation, a partial differential equation that filters image noise while enhancing region boundaries. He is currently interested in visual recognition and in visual analysis of behavior. In the early 2000s, Perona pioneered the study of visual categorization. Currently, in collaboration with colleagues Michael Dickinson and David Anderson, he applies machine vision to measuring and analyzing the behavior of laboratory animals.
Perona is the recipient of the 2013 Longuet-Higgins Prize and of the 2010 Koenderink Prize for fundamental contributions in computer vision. He is the recipient of the 2003 Institute of Electrical and Electronics Engineers–Conference on Computer Vision and Pattern Recognition best paper award. He is also the recipient of a 1996 NSF Presidential Young Investigator Award.