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Understanding and treating complex eye movement disorders like strabismus has long been a challenge for clinicians. Now, researchers at George Mason University are pioneering a new approach using robotics and artificial intelligence to engineer a better future for vision care.
Ningshi Yao, an assistant professor in the Department of Electrical and Computer Engineering, has been awarded a prestigious $1.17 million R01 grant to lead a groundbreaking four-year project. The award comes from the joint National Science Foundation (NSF) and National Institutes of Health (NIH) "Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH)" program.
The funded project, "Study Coordinated Human Eye Movement and Strabismus Using a Novel Artificial Muscle-Driven Robotic Eyes," will be conducted in collaboration with co-investigators Qi Wei and Quentin Sanders from George Mason’s Department of Bioengineering and consultant Joseph Demer in the Stein Eye Institute at the University of California, Los Angeles.
At the core of the research is the creation of robotic eyes powered by artificial muscles that replicate the precise, coordinated movements of human eyes. “Strabismus affects more than 18 million Americans, yet current treatments often fall short, with success rates ranging from 30 to 80%,” said Yao. “Our goal is to use robotic systems and artificial intelligence to better understand how the eyes work—and ultimately improve how we diagnose and treat these disorders.”
The research team will build robotic eyes that closely mimic human biomechanics and use them as tools to study the underlying causes of strabismus. These systems will allow for a level of control and repeatability not possible in human subjects, offering a unique window into how eye muscles and connective tissues—especially the so-called “pulleys”—work together to guide vision.
To make the robotic system truly intelligent, the project will also apply reinforcement learning, a type of artificial intelligence, to discover how humans naturally control eye movements. By training the robots with real patient data and expert-informed objectives, the team hopes to reverse-engineer the strategies humans use—leading to better understanding and new treatment pathways.
In the final phase of the project, the team will integrate patient-specific data into the robotic system to simulate different surgical outcomes. This will allow ophthalmologists to test and refine treatment strategies before operating, increasing precision and improving long-term results.
The project’s impact extends beyond eye health. The robotic muscle actuators and control models developed here could advance robotics, AI, biomechanics, and even the design of soft, adaptive machines.
In addition to scientific discoveries, the research team will build educational tools and training platforms using the robotic eyes, helping to prepare the next generation of vision specialists.