Meta Partners With Five US Universities to Accelerate Medical and Scientific Breakthroughs

We believe the future is for everyone, including America's universities, professors, students, and the communities who benefit from their research. That's why Meta is bringing Superintelligence models, research funding, and direct researcher collaboration to academia through partnerships with five US universities: California Institute of Technology, The Ohio State University College of Medicine, Louisiana State University, Indiana University, and UTHealth Houston.

We're expanding our academic partnerships by granting $2 million across these five schools to support research that uses our models to accelerate breakthroughs in medicine, physics, chemistry, biology, computer science, and mathematics.

In medicine and healthcare, researchers will work on a diverse set of projects using Meta's models, glasses, and mixed meality headsets to address existing gaps in medicine and healthcare. Here are a few examples of how they're being used:

Monitoring for Infant Tracheostomies

When tracheostomy tubes become dislodged in infant patients, it's a life-threatening emergency compounded by the fact that babies with tracheostomies can't cry out for help. And continuous direct observation by trained staff isn't always possible.

Dr. Michael Dunham from Louisiana State University is leading the Eyes-On project, which is developing a computer vision system to continuously detect tracheostomy tube displacement and signs of distress in infants who cannot reliably vocalize. The system is exploring usage of our open weight SAM models for tracking and is designed for integration with bedside cameras and edge computing. A proof-of-concept has been published, with more work to come.

Conversational AI for Dementia Care

People with dementia often experience communication difficulties that standard conversational AI systems handle poorly, leading to frustration rather than support. Dr. David Crandall at Indiana University is developing a project that aims to develop multimodal AI methods for analyzing conversations involving older adults living with dementia, and to use this understanding to help conversational agents - including social robots - adapt their interactions to individual users. The research tests whether AI systems can be made sensitive to the communication patterns of people with cognitive differences.

Identifying Heart Failure Risk Earlier

Heart failure with preserved ejection fraction (HFpEF) accounts for roughly half of all heart failure cases, but it can be difficult to recognize early - its symptoms overlap with those of obesity and other common conditions, so formal evaluation often begins only after clinical suspicion has developed.

At The Ohio State University College of Medicine, AI researcher Dr. Yuan Xue is leading a project with cardiologist Dr. Yuchi Han and AI researcher Dr. Xia Ning to investigate how Meta's open-weight models can help predict future HFpEF risk using routine abdominal CT scans, longitudinal medical records, and ECG data when available. The team is designing the model to handle missing data, since real-world clinical practice rarely provides a complete set of inputs.

You can read more on these projects on our Research Blog , and we look forward to sharing more as these projects get underway.