Topic: ML/AI

Research Projects

Rather than aiming to one day restore natural vision, we might be better off thinking about how to create practical and useful artificial vision now.

Rather than predicting perceptual distortions, one needs to solve the inverse problem: What is the best stimulus to generate a desired visual percept?

How does the brain extract relevant visual features from the rich, dynamic visual input that typifies active exploration, and how does the neural representation of these features support visual navigation?

Neuromorphic event-based vision sensors may soon power low vision aids and retinal implants, where the visual scene has to be processed quickly and efficiently before it is displayed.

Researchers Interested in This Topic

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CS

Kimia Afshari
MS Student

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CS

Sriya Aluru
ERSP Scholar

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Michael Beyeler
Assistant Professor

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CS

Cheng Han (Johnson) Chan
Research Assistant

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CS

Justin Chung
Research Assistant

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CS

Robert Gee
Research Assistant

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CS

Jacob Granley
PhD Student

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CS

Ethan Meade
DIMAP Student

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CS

Galen Pogoncheff
PhD Student

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CCS

Laya Pullela
Research Assistant

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CS

Shivani Sista
Research Assistant

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ICB

Amirali Vahid
Postdoctoral Scholar

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CS

Aiwen Xu
PhD Candidate