We are an interdisciplinary laboratory working on the border between human cognition and machine intelligence.
Principal Investigator: Mingbo Cai, Assistant Professor, 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 may accept one PhD student for Fall 2027, apply here (through cognitive and behavioral neuroscience track)! Feel free to reach out to Mingbo explaining your interest.
Lab updates:
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In this paper, we show that predicting future visual input provides sufficient teaching signal for a neural network model with access to similar signal (continuous stream of visual input and knowledge of self-motion) available to infants to learn to perceive space in 3D and segment and localize objects. Congrats to the lead authors John and…
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Iba developed a new AI-based pipeline that automatically generates time courses of annotation of people’s behavior in videos, which will facilitate annotation of videos in developmental research. Continue reading
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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 while varying the weather and…