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Ralf Haefner is an Associate Professor in the Department of Brain and Cognitive Sciences at the University of Rochester, with additional affiliations in the Department of Physics and Astronomy and the Department of Computer Science. He is also a member of the Center for Visual Science and the Goergen Institute for Data Science. Haefner joined the University of Rochester in 2014 as an Assistant Professor and was promoted to Associate Professor in 2022. His primary scientific interest lies in understanding how the brain forms percepts and uses them to make decisions, especially in the visual domain. In particular, he focuses on how the brain's perceptual beliefs about the outside world are represented by the responses of populations of cortical neurons, employing tools from machine learning to construct mathematical models that explain neural responses and behavior. His research interests include perceptual decision-making, probabilistic inference, selective attention, neural population encoding and decoding, and depth perception and processing of binocular disparity.
Haefner earned his D.Phil. in theoretical physics from Oxford University in 1999. He subsequently obtained an MPA from the Harvard Kennedy School of Government in 2001 as a McCloy Scholar. His postdoctoral positions included roles at the National Eye Institute from 2004 to 2009 and the Max Planck Institute for Biological Cybernetics from 2009 to 2011. He served as a Swartz Fellow at Brandeis University from 2011 to 2014 and as a Visiting Research Fellow at Harvard Medical School from 2013 to 2014. Prior to his academic career, he worked as an Associate at McKinsey & Co. from 2002 to 2003. Haefner has authored or co-authored numerous publications in peer-reviewed journals, including key papers such as "Perceptual Decision-Making as Probabilistic Inference by Neural Sampling" in Neuron (2016) and works in Nature Neuroscience, eLife, and PLoS Computational Biology. He maintains an active research program through his laboratory at the University of Rochester.
Dive into the University of Rochester's groundbreaking study showing how learning boosts neuron coordination in the visual cortex, challenging old theories and impacting education, disorders, and AI.
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