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I’m a Postdoctoral Fellow in the Department of Cognitive Science at Johns Hopkins University. My research combines vision science with intuitive physics, focusing on how we derive an understanding of physical laws from our sensorimotor experiences.

I completed my PhD at Brown University, where I explored how the brain internalizes concepts like gravity, mass, and momentum through everyday interactions—think of a little leaguer perfecting their pitch or a server skillfully balancing dishes. By employing methods such as computational modeling, motion tracking, psychophysics, and virtual reality, I investigate how our perceptual systems help us navigate complex physical environments and how these insights can inform both cognitive science and artificial intelligence.

🆕 New paper in Journal of Neurophysiology
Relational dynamics inform predictive motor planning and perception
Using a hybrid VR + real-object setup, we show that purely visual collision dynamics shape both how people plan their lifts and how heavy the objects feel. Relational motion cues create a dynamic weight illusion: objects that “should” be heavier based on the collision feel heavier, even when their physical mass is identical.
Read the paper