Blog

GARDE-Chat is an AI-powered, no-code platform that enables researchers to build chatbot-based digital health interventions at scale. Developed by Professors Guilherme Del Fiol and Ken Kawamoto, the tool supports rule-based and LLM-driven chatbots and has already powered more than 15 projects—including large trials reaching up to 100,000 patients. By improving access to evidence-based services and helping secure over $35 million in federal funding, GARDE-Chat demonstrates how AI can make healthcare interventions more scalable, effective, and widely accessible.

At the University of Utah’s Utah NeuroRobotics Lab, artificial intelligence is driving breakthrough research in bionic technology. Led by Jacob A. George, the team develops AI-powered prosthetic and assistive devices that restore movement and sensation for individuals with neuromuscular impairments. Their work blends engineering, medicine, and machine learning to create intuitive, life-changing technologies—many of which have already produced compelling patient outcomes and inspired new startup ventures. Through deep interdisciplinary collaboration, the lab is shaping the future of bionics and redefining what’s possible in assistive healthcare.

A multidisciplinary team at the University of Utah is using artificial intelligence and computer vision to develop advanced imaging biomarkers that enhance cancer diagnosis, prognosis, and treatment planning. Led by Beatrice Knudsen, one key research direction focuses on creating computational tissue biomarkers, while the broader team integrates histopathology, radiology, and clinical data into multi-modal algorithms. Supported by major federal grants and cross-department collaboration, this work is advancing precision cancer care and generating impactful publications and training opportunities.

University of Utah Department of Internal Medicine Research Associate Professor George G. Vega Yon and his software development team use agentic AI as a human-guided co-developer to accelerate CDC-funded public health projects. AI assists with coding, testing, and rapid prototyping while researchers remain fully in the loop, enabling faster responses to real-world needs such as measles outbreak modeling.

Jess Tate of the SCI Institute shares about the National Data Platform (NDP), an NSF-funded collaboration designed to transform how researchers access, share, and analyze data. By connecting data sources, tools, and compute resources in a federated ecosystem, NDP makes data more findable, accessible, interoperable, and reproducible (FAIR)—advancing collaborative, scalable, and trustworthy science.