I study the human visual system with a focus on investigating how we integrate sensory information to make perceptual judgments, how we exploit statistical regularities in the environment, and how we adapt when these statistical regularities are altered or when new statistical contingencies are introduced. My research addresses a broad spectrum of topics ranging from basic questions about visual signal detection, visual search, perceptual learning, and neural coding to potential clinical applications in assessing the visual performance of retinopathic patients and radiologists and evaluating the potential impact of training interventions. Central to my approach are the treatment of vision as a problem of probabilistic inference and the use of ideal observers as a standard against which to compare human performance.

Melchi Michel received his Ph.D. from the Department of Brain and Cognitive Sciences at the University of Rochester in 2007. He was a postdoctoral fellow in the Center for Perceptual Systems at the University of Texas at Austin from 2007-2012 and joined the Rutgers faculty in 2012.