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

Sriya Aluru
ERSP Scholar

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Michael Beyeler
Assistant Professor

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CS

Ashley Bruce
MS Student

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CS

Alexander Chau
Research Assistant

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CE

Harshita Gangaswamy
ERSP Scholar

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CS

Robert Gee
Research Assistant

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CS

Anand Giduthuri
Research Assistant

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CS

Jacob Granley
PhD Student

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CE

Sahil Naik
Research Assistant

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CS

Alex Rasla
BS/MS Student

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CS

Lucas Relic
MS Student

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CS

Vanessa Salgado Zavaleta
ERSP Scholar

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CS

Shivani Sista
ERSP Scholar

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CS

Madori Spiker
MS Student

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CS

Gita Supramaniam
ERSP Scholar

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CS

Eyob Teshome
BRAIN Scholar

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ICB

Amirali Vahid
Postdoctoral Scholar

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CS

Francie Wei
Research Assistant

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CS

Aiwen Xu
PhD Candidate