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

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.

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.

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.

We evaluate head- and cane-mounted cameras for blind navigation and show that combining both yields superior spatial perception, guiding the design of hybrid, user-aligned assistive systems.

Our interview study found a significant gap between researcher expectations and implantee experiences with visual prostheses, underscoring the importance of focusing future research on usability and real-world application.

We introduce VisionAI, a mobile application designed to enhance the in-store shopping experience for individuals with vision impairments.

We present a series of analyses on the shared representations between evoked neural activity in the primary visual cortex of a blind human with an intracortical visual prosthesis, and latent visual representations computed in deep neural networks.