The University of Utah One-U Responsible Artificial Intelligence Initiative (One-U RAI) at the Scientific Computing and Imaging (SCI) Institute has named 12 new faculty fellows, nearly double the number of awardees announced last year. This expansion underscores the university’s commitment to rapidly advancing ethical, interdisciplinary AI research that addresses real-world challenges, from expediting emergency medical care to protecting the West’s water supply to systematically embedding ethics in AI education.
Penny Atkins, SCI Institute director of research and science, said the increase brings representation from eight new departments, expanding opportunities for cross-campus collaboration. “We continue to be impressed by both the quantity and quality of applicants and are so excited to see this program grow,” Atkins said. “We hope to expand engagement across campus to include additional departments and colleges in future years.”
The new faculty fellows span 5 colleges and 10 departments and their work is expected to drive progress in the initiative’s thematic areas: environment, health care and wellness, and teaching and learning. Awards may be used flexibly and amount to 25% of a fellow’s base salary, with a maximum award of $75,000 and a minimum award covering the average annual cost of a graduate student in the fellow’s department. Fellowships are awarded for three years and may be renewed following review. Read more about the program.
Five of the new fellows hail from the John and Marcia Price College of Engineering. They are:
Ziad Al-Halah
Assistant Professor; Kahlert School of Computing
Thematic Area: Teaching & Learning
Ziad Al-Halah develops efficient multimodal AI assistants that learn with constrained resources and understand text, images, and video. His research addresses key environmental and accessibility challenges in modern AI by reducing supervision costs, lowering power consumption, and creating practical tools for education. For example, his AI assistants can separate audio-visual sources to generate clearer captions for hearing-impaired students or analyze classroom recordings to help users quickly locate specific moments. “I want to enrich students’ and instructors’ experiences and help shape AI as a force for the public good,” Al-Halah said. He also plans to expand this work through a new course on multimodal AI. “By combining cutting-edge research with ethical considerations, my goal is to prepare students not only to innovate in AI, but also to apply it responsibly.”
Heather Holmes
Associate Professor; Department of Chemical Engineering
Thematic Areas: Environment + Health Care & Wellness
Researchers increasingly use AI for environmental modeling, but physics-based models still outperform AI for predicting extreme events. Heather Holmes wants to bridge that gap. “My domain science background is critical to develop responsible AI tools to protect human health and the environment,” she said. Holmes, who earned her master’s and PhD in mechanical engineering from the U, used her National Science Foundation CAREER award to create a course on high-performance computing and numerical weather prediction. She also co-founded Trace Air Quality, a U startup that provides advanced warnings when pollution events threaten air quality. Through the fellowship, Holmes will use AI to improve wildfire emissions estimates, winter air-quality forecasts, and exposure modeling for extreme events like smoke and heatwaves, strengthening early warning systems and protecting public health.
Ryan Johnson
Assistant Professor; Department of Civil and Environmental Engineering
Thematic Area: Environment
Ryan Johnson leverages AI to safeguard water resources in the drought-prone western U.S., focusing on snow mapping, streamflow monitoring, and predictive modeling to inform water management. “My work is driven by the need to integrate technical innovation with long-term sustainability,” he said. He uses AI-optimized monitoring stations, machine learning, and edge computing—processing data at potentially remote stations, as opposed to the cloud, to allow for real-time analysis. Johnson, who holds a PhD in civil and environmental engineering from the U, recently developed a hydroinformatics course that covers data science and computing while grounding students in responsible AI. As a fellow, he will develop auditable AI models for the Upper Colorado Basin—incorporating demographic data to prevent social or economic biases in decision-making—and create open-source tools to push his field forward.
Mike Kirby
Professor; SCI Institute and Kahlert School of Computing
Thematic Areas: Environment + Health Care & Wellness + Teaching & Learning
Mike Kirby brings decades of experience in computing and interdisciplinary research to explore how AI can fairly and transparently serve the public good. His work spans technical innovation and humanistic inquiry, from developing AI-driven models to study voting patterns to co-authoring an in-progress book with inaugural distinguished visitor David Danks on applying medieval philosophy to AI and ethics. “From my early technical contributions in AI development within the engineering sciences to more recent interdisciplinary efforts, I have sought collaborative projects that integrate both technical depth and humanistic breadth,” Kirby said. As a fellow, he will deepen research on AI governance in health care, explore how responsible AI can address environmental challenges, and create educational tools that prepare students, policymakers, and the public to think critically about AI.
Marina Kogan
Assistant Professor; Kahlert School of Computing
Thematic Areas: Environment + Health Care & Wellness
Marina Kogan develops AI systems to extract insights from massive social media datasets, helping officials respond to natural disasters and combating health misinformation. “Applying out-of-the-box AI algorithms without accounting for social context produces biased results, rarely useful to stakeholders,” she said. “I develop AI-based approaches for finding actionable insights in the data deluge.” Kogan co-advises postdoctoral fellow Di Wang, whose project uses natural language processing and computer vision to guide disaster recovery. As a faculty fellow, Kogan will work with Huntsman Cancer Institute colleagues to analyze misconceptions about genetic cancer risk in online forums and evaluate school sun-safety policies aimed at preventing skin cancer. She’ll also build collaborations in mental health, where she can apply essential expertise in developing safe systems that maintain data privacy.