James Kubricht

PhD, Computational Cognition (UCLA) MS, Cognitive Psychology (UCLA) BS, Physics (UT Austin)

I received a BS in Physics from UT Austin in 2013 and a PhD in Computational Cognition from UCLA in 2018. I am currently working as a postdoctoral researcher in computer vision at GE Research. Specifically, I am interested in how computer vision systems can be utilized to extract meaningful information and infer latent properties in dynamic physical (and social) scenes. Until now, my research has focused on how people perceive and reason about the dynamics of complex physical entities, such as non-solid substances, and how the brain combines noisy perceptual inputs with intuitive knowledge about physical principles to make predictions about how a system might behave in the future.

I am particularly interested in how dynamic information is utilized by the human brain, and when this type of information is particularly useful. I have explored human predictions and judgments about physical situations in 2D experiments as well as in 3D virtual environments where properties of the world can be controlled and manipulated. My computational approach to modeling human performance has followed a Bayesian framework, although I have also utilized data-driven (machine learning) approaches to explain behavioral data.

James’s Work

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