Noga Zaslavsky

Noga Zaslavsky is an Assistant Professor of Psychology at New York University, USA (2024–present), previously holding positions at the University of California, Irvine (2023–2024) and a Postdoctoral Fellowship at MIT (2019–2023). His research focuses on computational principles underlying language, learning, and reasoning, integrating machine learning and information theory. Key interests include optimality principles in semantic systems, neural network learning, and the interplay between language and cognition.

Education and affiliations: Ph.D. work reflected in his 2020 thesis on information-theoretic principles in semantic systems. Lab affiliation with the Information Cognition Lab (InfoCogLab), evident from GitHub contributions.

Research emphasizes efficient compression in communication systems, with notable work on color naming evolution (e.g., PNAS 2018, awarded the ELSC Prize). His recent projects bridge semantics/pragmatics in emergent communication and neural alignment between artificial and human systems.

Grants and advising: No explicit grants listed, but extensive publications suggest active research funding. Advising students not explicitly listed here.

Labs/Teams: Primary affiliation with NYU Psychology Department and InfoCogLab, collaborating on projects like the Information Bottleneck model for color naming systems.