We are an interdisciplinary laboratory working on the border between human cognition and machine intelligence. We belong to Department of Psychology, University of Miami
By building computational models and conducting experiments to study human behavior and brain imaging data, we aim to understand the computation underlying learning, decision making, and spontaneous thoughts. Along the way, we contribute new tools to the community. The main goal of computational models in our lab is not to simulate the system, but rather to understand the high-level computation that the system realizes, and the functionality these computations fulfill.
We also take inspiration from human perception, cognition, and development to build deep learning methods that learn models of the world with similar constraint faced by infants.
We will be accepting PhD student for Fall 2025, apply here in September (through cognitive and behavioral neuroscience track)!
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A lot of computation takes place from the image falling on our retina to the brain forming a cognitive map. An important computation is inferring the geometry structure of scenes. Here we let people watch videos of cars navigating in virtual towns, and modeled the synchronized neural activity across people…
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In the work led by Wei Chen, we asked whether recurrent neural network can improve the ability of predicting psychiatric symptoms from people’s sequential decision making behavior compared to using parameters extracted by reinforcement learning models. Preprint to come out soon! In the work led by John Day and Tushar…
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PreprintAs part of human core knowledge, the representation of objects is the building block of mental representation that supports high-level concepts and symbolic reasoning. While humans develop the ability of perceiving objects situated in 3D environments without supervision, models that learn the same set of abilities with similar constraints faced…