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Active Research Projects
Neural network modeling of visual perception and cognition
Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. We seek to develop neural network models that can meet real-world computational challenges faced by biological visual systems and that can also explain detailed patterns of brain and behavioral responses.
Development of statistical inference and visualization methods
Computational neuroscience is entering a new era, where big models meet big data. We develop statistical inference and visualization techniques that help us connect theory and experiment, enabling us, for example, to adjudicate among many candidate neural network models using brain-activity measurements acquired with functional imaging and electrophysiological recordings in animals and humans.
News
Welcome Dr. Amir Farzmahdi!
The lab welcomes new postdoctoral researcher, Dr. Amir Farzmahdi, who joined January 16, 2025 to work on recurrent models of visual inference in the primate brain.
New Publication in PNAS
A new paper, “The topology and geometry of neural representations” led by Dr. Baihan Lin is now published in PNAS!
Welcome Dr. Fan Cheng!
The lab welcomes postdoctoral researcher, Dr. Fan Cheng, who joined us on August 16th, 2024 to work on computational models of visual illusions.