Rate My Professor Tomer Ullman

As a cognitive scientist, Tomer Ullman focuses on common-sense reasoning and constructing computational models to explain high-level cognitive processes and the acquisition of new knowledge by children and adults. His investigations target how intuitive theories of agents and objects form, offering functional and algorithmic accounts of their learning—key to comprehending human intelligence and enhancing human-like artificial intelligence. Core interests include computational cognitive models, child development, judgment and decision making, and hierarchical reasoning. Ullman has been honored with the Best Paper Award at the 2012 International Conference on Development and Learning for “Sticking to the evidence? A computational and behavioral case study of micro-theory change in the domain of magnetism” and served as a Jacobs Foundation Research Fellow from 2022 to 2024.

Ullman’s publications feature prominent contributions such as the chapter “Bayesian Models of Conceptual Development: Learning as Building Models of the World” (Annual Review of Developmental Psychology, 2020, with Joshua B. Tenenbaum), “Bayesian models of cognitive development” (Bayesian Models of Cognition, 2024, with Elizabeth Bonawitz), “The capacity limits of moving objects in the imagination” (Nature Communications, 2025, with H. Balaban), “Physics versus graphics as an organizing dichotomy in cognition” (Trends in Cognitive Sciences, 2025, with H. Balaban), and “People evaluate agents based on the algorithms that drive their behavior” (Open Mind, 2025, with E. Bigelow). These works significantly influence cognitive science, developmental psychology, and artificial intelligence by integrating empirical findings with formal modeling.