Research

Main approaches for the design of a visual prosthesis (Fernandez, 2018) include retinal (A), optic nerve (B), lateral geniculate nucleus (LGN, C), and cortical approaches (D).

Rethinking sight restoration through models, data, and lived experience.

We experience the world through rich and varied forms of vision. For people who are blind or have low vision, existing tools and technologies often fall short of supporting this diversity of experience. Our goal is to understand how biological and artificial vision systems work, and to use those insights to design neurotechnologies that expand access to visual information and support greater independence.

The Bionic Vision Lab tackles this challenge at the intersection of neuroscience, psychology, and computer science. We combine behavioral experiments, VR/AR, and neurophysiological methods (EEG, TMS, physiological sensing) with computational modeling, machine learning, and computer vision. This allows us to connect brain, behavior, and technology; asking how perception supports real-world action, and how artificial systems can interface with the brain to restore or augment visual function.

Our work spans three interconnected research areas:

  • Understanding perception and behavior. We study how people with low vision or blindness perceive and navigate complex environments, using psychophysics, immersive VR, and ambulatory head/eye/body tracking to link perception to real-world function.

  • Modeling neural systems and prosthetic vision. We develop biophysically informed and machine learning models of retinal and cortical stimulation, predicting what visual prosthesis users see and designing algorithms to optimize stimulation strategies.

  • Building intelligent assistive technologies. We build real-time XR testbeds and computer vision–based assistive tools, using insights from human and animal vision to power the next generation of wearable and implantable devices.

This integrative approach welcomes students with diverse strengths: some focus on human behavior and perception, others on neural systems and computation, and others on designing interactive technologies. Together, they work toward a shared goal: creating tools and interfaces that bring meaningful, functional vision within reach.

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.

Visual Prosthesis Computer Vision Immersive Technology (VR/AR/MR)

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

Visual Prosthesis Machine Learning Psychophysics

What do visual prosthesis users see, and why? Clinical studies have shown that the vision provided by current devices differs substantially from normal sight.

Visual Prosthesis Computational Neuroscience Psychophysics

A nuanced understanding of the strategies that people who are blind or visually impaired employ to perform different instrumental activities of daily living (iADLs) is essential to the success of future visual accessibility aids.

Assistive Technology Blindness & Low Vision Psychophysics

This research explores the integration of computer vision into various assistive devices, aiming to enhance urban navigation and environmental interaction for individuals who are blind or visually impaired.

Assistive Technology Computer Vision Immersive Technology (VR/AR/MR)

How are visual acuity and daily activities affected by visual impairment? Previous studies have shown that vision is altered and impaired in the presence of a scotoma, but the extent to which patient-specific factors affect vision and quality of life is not well understood.

Blindness & Low Vision Visual Perception Psychophysics

Understanding the visual system in health and disease is a key issue for neuroscience and neuroengineering applications such as visual prostheses.

NeuroAI Computational Neuroscience

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?

Computational Neuroscience Machine Learning

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.

Computer Vision NeuroAI