Uri Hasson (CV) grew up in Jerusalem. As an undergrad he studied philosophy and cognitive sciences at the Hebrew University. He completed his Ph.D. in Neurobiology at the Weizmann Institute in Israel and was a postdoctoral fellow at NYU before moving to Princeton. He is currently a Professor in the Psychology Department and the Neuroscience Institute at Princeton University. His research program aims to understand how the brain processes real-life complex information and interacts with the environment; with a focus on integration of complex information over time and the interaction between two individuals and two brains during natural communication. Faculty Page

Liat is a developmental psychologist. As M.A. student at the Goethe-University, Frankfurt, and during her PhD at the Hebrew University, Jerusalem, she studied the role of motivation in learning. During her postdoctoral years as a fellow at the Martin Buber Society she started to search for theoretical and scientific tools from outside the field of psychology that can be applied to developmental research. She is currently interested to better understand the neuronal processes underlying development and learning.
 

Elise grew up in Rochester, NY and earned her B.A. from Williams and her Ph.D. from Berkeley. She is interested in how our brains extract patterns from the environment to facilitate communication. Her dissertation research investigated efficient mechanisms for understanding the multisensory world, including statistical learning, statistical summary (i.e., “gist” processing), prediction, and adaptation. Personal website

elise.piazza@gmail.com

Meir studies the neuronal mechanisms underlying real-life learning and understanding. His research aims to improve teaching and learning in STEM using neuroimaging, brain decoding and machine learning methods. Before coming to Princeton, he obtained a Ph.D. from the Weizmann Institute of Science in Israel, focusing on problem-solving and on mind-wandering, and spent a couple of years doing machine learning in industry. Personal website.

Ariel uses cognitive computational models to try to understand high-level cognition. More specifically, he is interested in constraining computational models of cognition by brain data. His current focus is on using ECoG and speech data to map concepts in the neuronal space.

ariel.y.goldstein@gmail.com

Sam studied cognitive science and philosophy at Johns Hopkins University, earned a master’s degree at the University of Trento in Italy, and received his PhD from Dartmouth College. Sam is interested in using naturalistic experiments (e.g., watching movies, listening to stories) and multivariate statistics to investigate how our brains construct a semantic understanding of the world. His current work is focused on the neural machinery supporting action understanding, modeling shared and idiosyncratic responses across brains, and how we use language to transmit our brain states to others.

snastase@princeton.edu

Sebastian is interested in our unique ability to retrieve vivid information from the past.

He currently uses electrophysiology and behavioral experiments to understand how our brain guides us through extended episodic memories.

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s.michelmann@princeton.edu

Claire Chang grew up in Taiwan and got a bachelor degree in law, masters in linguistics, and PhD in cognitive neuroscience. During her PhD years, she spent twenty months in INSERM-CEA Cognitive Neuroimaging Unit in France as a visiting fellow. She has studied in different aspects of language processing, e.g. lexical tone, visual processing in reading, and syntax. She now works on communication in a broader sense, namely, inter-personal interaction, especially the dynamical coupling between two brains using the hyperscanning technique.

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hcchang73@gmail.com

Jamal Williams is a Ph.D. candidate in the Princeton Neuroscience Institute currently being advised by Kenneth Norman, Uri Hasson, and Elizabeth Margulis. Jamal uses neuroimaging and computational modeling to investigate the neural mechanisms underlying the complex relationship between music and memory. Some advantages of using music to study the brain is that music is both ecologically valid and it is theoretically well-defined at many levels. Jamal received his B.A. in Psychology from the University of Memphis where he used artificial intelligence, computational modeling, and music to understand patterns of learning in humans. Jamal plans to eventually extend his research to different sub-populations such as infants and across cultures, to better understand how music-related memory for real-world events develops within and across brains.

jamalawilliams@gmail.com

Zaid has a bachelor’s in Computer Science and is working on a master’s degree specializing in Machine Learning. He is interested in applying Machine Learning techniques in Neuroscience research. His current focus in on using ECoG data and neural networks to understand semantic representations in the brain.

zzada@princeton.edu

Bobbi grew up in Wisconsin. She completed her bachelor's degree in neurobiology and communication science & disorders at the University of Wisconsin. She ultimately wants to study neurorehabilitation techniques following Traumatic Brain Injuries and Stroke in graduate school while pursuing her PhD in neuroscience.

baubrey@princeton.edu

Eric Ham completed his undergraduate degree at Princeton University in 2019, where he majored in Electrical Engineering with an emphasis on Data and Information Systems and received certificates in Applications of Computing and Robotics and Intelligent Systems. Eric is interested in applying his experience in data science and machine learning to problems in the life sciences, with his current focus being the modeling of temporal and spatial relationships in the brain with neural networks. When he is not running models or debugging code, Eric enjoys dancing, making music and spending time in nature. 

eric.michael.h@gmail.com

Colton, a senior at Princeton originally from North Carolina, is pursuing a bachelor's degree in neuroscience with certificates in computer science and machine learning. Colton currently works with ECoG data collected during naturalistic speech production and comprehension to investigate the role of context in language processing. He is interested in applying techniques from the field of natural language processing to inform how we study the brain. 

casto@princeton.edu

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S.H.P.Collin@tilburguniversity.edu

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cab2304@columbia.edu

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yulia.lerner@gmail.com

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mlnguyen@princeton.edu

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az2604@columbia.edu

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