Rate My Professor Ken Norman

Kenneth A. Norman is the Huo Professor in Computational and Theoretical Neuroscience, Professor of Psychology and Neuroscience, and Chair of the Department of Psychology at Princeton University. He directs the Princeton Computational Memory Lab and holds affiliations with the Princeton Neuroscience Institute and the Cognitive Science program. Norman received his B.S. with distinction in Symbolic Systems from Stanford University in 1993, M.A. in Psychology from Harvard University in 1996, and Ph.D. in Psychology from Harvard University in 1999, advised by Daniel Schacter. His thesis focused on differential effects of list strength on recollection and familiarity. From 1999 to 2002, he was an NIH NRSA postdoctoral fellow in Randall O’Reilly’s lab at the University of Colorado, Boulder. Norman joined Princeton University in 2002 as Assistant Professor of Psychology, was promoted to Associate Professor in 2008 and Professor in 2013, served as Associate Chair from 2012-2014 and 2016-2017, became Chair in 2017, and was named Huo Professor in 2019.

Norman's research employs computational modeling to elucidate brain mechanisms underlying learning and memory. His lab tests these models using neuroimaging—fMRI and EEG—to decode thoughts as individuals learn and remember, investigating learning rules for memory modification, sleep's role in learning, experience segmentation into events, collaboration among episodic, semantic, and working memory systems, and intentional forgetting. He develops machine learning techniques for neural pattern analysis, data mining algorithms to isolate signatures of thoughts and memories, and real-time neurofeedback methods. Norman has earned the Psychonomic Society Mid-Career Award (2023), Fellow of the Society of Experimental Psychologists (2018), Fellow of the Association for Psychological Science (2018), Fellow of the Psychonomic Society, Princeton Graduate Mentoring Award (2016), President’s Award for Distinguished Teaching (2007), and others. Key publications include “Beyond mind-reading: multi-voxel pattern analysis of fMRI data” (Trends in Cognitive Sciences, 2006), “Modeling hippocampal and neocortical contributions to recognition memory: a complementary-learning-systems approach” (Psychological Review, 2003), “Discovering event structure in continuous narrative perception and memory” (Neuron, 2017), “A context maintenance and retrieval model of organizational processes in free recall” (Psychological Review, 2009), and “Category-specific cortical activity precedes retrieval during memory search” (Science, 2005). His work has profoundly influenced cognitive neuroscience, with over 28,000 citations.