Biography

Vision is an active process. Far from being passive recipients of external information, our visual systems are constantly generating meaning by combining sensory information with internal beliefs about the structure of the world around us. From the perspective of Bayesian statistics, these beliefs correspond to perceptual priors. My research centers around uncovering the hidden structure of subjective probability distributions and understanding the role that they play in perception and cognition. In particular, I investigate visual decision-making at the level of behavior, computation, and neural (biological) implementation. I am particularly interested in understanding the information-theoretic tradeoffs that shape our perceptual inferences.

For a representative example of my work probing visual memory priors, see my work in PNAS. For another example of my work exploring the neural (biological) basis of Bayesian inference during visual decision making, see my more recent work in PNAS. I also investigate how biological vision differs from computer vision systems. For a representative example of this work, see my oral presentation and paper in NeurIPS 2021. I am currently exploring the information-theoretic tradeoffs that govern how humans communicate about visual percepts using the Information Bottleneck (IB) Principle.

I completed my Ph.D. in Thomas Griffiths’ Computational Cognitive Science Lab at UC Berkeley in August of 2018. Prior to completing my Ph.D., I completed an M.S. in Computer Science (EECS), also at UC Berkeley. I then joined Princeton University as a postdoctoral researcher, where I developed experimental methods to estimate subjective probability distributions in visual memory. Next, I completed a postdoctoral fellowship at UT Austin in the Center for Perceptual Systems (CPS), where I worked in Robbe Goris’ group. I am currently a postdoctoral associate in the Brain and Cognitive Sciences Department (BCS) at MIT, where I am working with Roger Levy and Noga Zaslavsky on applications of the Information Bottleneck (IB) Principle. I am also a visiting scholar affiliated with the Department of Psychology at NYU.