Thematic Area:​ Teaching and 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.”

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Thematic Areas: Health Care and Wellness​, Teaching and Learning

Emad Awad advances responsible AI in health care, particularly in time-sensitive, high-stakes emergency care. By combining data science with bedside insight, he develops transparent and equitable predictive tools, including AI models to forecast emergency department wait times and support rapid clinical decision-making. A cornerstone of his work is the Utah Emergency Department Database, a first-of-its-kind data platform that helps emergency care teams make timely, informed decisions. He is currently piloting this tool at the U and plans to deploy it nationally. “I aim to ensure that predictive tools are transparent, equitable, and clinically meaningful,” Awad said. Through One-U RAI, he will also strengthen training pathways in ethical AI. “I am committed to preparing future health professionals to critically evaluate and responsibly apply AI in practice."

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Thematic Area: Environment

Mickey Campbell uses AI to better understand forests and give wildland firefighters tools for real-time decisions. Campbell, who completed his PhD in geography from the U, uses image and lidar data collected from the ground, air, and space to study Earth systems and how we interact with them. He applies AI to monitor piñon–juniper woodlands, an ecologically important and climatically sensitive ecosystem that spans the West. Another focus, he said, is scalable, precise mapping of forest health changes over space and time. “Drought and insect outbreaks have triggered widespread die-offs, yet current monitoring relies on coarse, manually collected data,” he said. His AI models map tree mortality to track degradation in a changing climate. He also applies his expertise to wildfires, developing tools to enhance firefighter response and safety.

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Thematic Areas: Environment, Teaching and Learning​

Codding’s work applies machine learning and deep learning models to aid Indigenous-led conservation and restoration projects. He will work with community partners around the use of AI for understanding and addressing critical human-environmental challenges. “This will include building partnerships, inclusive training data sets, and models that responsibly represent the environmental management needs and goals of tribal members,” he said. Ultimately, he hopes to help inform restoration and conservation efforts that improve ecosystems and livelihoods in Utah.​

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Thematic Area: Teaching and Learning​

Kenneth Collins uses AI not just to create art but to investigate what it means to be human in a digital age. “Creative research is not peripheral but absolutely central to comprehending AI's reconstruction of human identity, authorship, and expression in the 21st century,” he said. Collins uses text, image, video, speech, music, and sound-generation algorithms to produce work that sparks dialogue about the ethical and aesthetic implications of AI across disciplines. His AI-driven artworks have been exhibited internationally, and he pioneered one of the first university courses in AI filmmaking and a companion festival for student work. Through the fellowship, he plans to position Utah as a leader by hosting interdisciplinary workshops, building a “living laboratory” for AI-human collaboration, and launching outreach initiatives that bring AI art experiences to underserved communities.

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Thematic Areas: Health Care and Wellness, Environment

Nina de Lacy is a physician-scientist and psychiatrist developing explainable AI (XAI) systems that predict health outcomes and show how they reach conclusions, making them trustworthy for doctors and patients. “In my lab, we maintain a relentless focus on translational relevance and acceptability from origin to edge,” de Lacy said. She uses real-world data from wearables, apps, and health records to identify patterns in everyday behaviors, like sleep or movement, that signal changes in health. She co-created RiskPath, open-source software that uses XAI to predict chronic diseases years before symptoms appear. As a fellow, de Lacy will strengthen data infrastructure, advance AI in mental health care, launch a center for XAI in digital health, and co-lead a project that maps personal exposure to environmental factors like temperature and air quality.

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Thematic Areas: Environment, Health Care and Wellness​

Freiling’s publications identify the challenges that algorithms pose in understanding online information environments, such as social media, where researchers don’t know who sees what. “For example, if we do not know who saw a message about climate change, we cannot measure its effect on people’s perceptions of climate change,” she said. She is advancing understanding of how this lack of access to data hinders theory building. Science communication is critical to advancing AI responsibly, she said, because it helps to reach diverse audiences affected by AI and identify ethical issues.

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Thematic Area: Health Care and Wellness​

French brings a foundational knowledge of AI and machine learning; a unique combination of skills related to neurorehabilitation, bioinformatics, and data science; and expertise related to patient-centered outcomes.​ She uses biomedical data and AI to examine complex patterns in rehabilitation and develop predictive models of outcomes, particularly for stroke recovery. “Curating a robust dataset is essential to setting the stage for my research goals and for ensuring the responsible application of AI to high-quality data in health care,” she said.

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Thematic Areas: Environment, Health Care and 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.

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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.

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Thematic Areas: Environment, Health Care and Wellness, Teaching and 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.

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Thematic Areas: Environment, Health Care and 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.

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Thematic Areas: Health Care and Wellness, Teaching and Learning

Polina Kukhareva is a clinical informaticist who uses AI to improve diabetes treatment. Her work focuses on developing rigorous, evidence-based methods that help clinicians choose the most effective medications for patients. Funded by the National Institutes of Health and university research initiatives, she uses large sets of health records to study treatment patterns, predict outcomes, and estimate how different medications affect patients. “I bring a unique perspective as a scientist trained in public health and biomedical informatics who works at the intersection of AI, real-world data, and health care implementation, strengthening the university’s commitment to diverse viewpoints and innovation,” Kukhareva said. As a fellow, she will expand research training through programs such as the Summer Program for Undergraduate Research and the Native American Summer Research Internship.

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Thematic Area: Teaching and Learning​

Li has developed and investigated numerous AI models in teaching and learning, including responsible large language models (LLMs) for scalable online-learning support. He focuses on the personalization of education through fair, accountable, and transparent AI tools and learning analytics grounded in rich learning theories. “I intend to collaborate on research and grant proposals promoting educational equity through AI and organize or contribute to venues to raise awareness of AI’s societal impacts among educators and students,” Li said.

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Thematic Area: Teaching and Learning​

Marasović develops and rigorously evaluates frontier AI models, such as LLMs, to empower people through effective AI-assisted decision-making, communication, and creativity. “I advocate for simulations where dynamic and complex interactions unfold over time, where risks are evident, and accountability is promoted, as in real-life decision making,” she said. “I will, as a faculty fellow, create a robust testbed to assess the readiness of LLMs and the human-AI collaboration methods developed by my lab, ultimately enhancing both their development and their ability to improve student learning.”

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Thematic Area: Teaching and Learning

“Embedded Ethics” programs that pair computer scientists with philosophers are gaining traction at top universities. Thi Nguyen, a nationally recognized expert in data ethics and the social impacts of technology, wants to bring a tailored version to the U. “One-sided pedagogies are usually flawed,” said Nguyen, who has appeared on The Ezra Klein Show and in Vox’s “2024 Future Perfect 50” list of innovators building a better future. “We’ll develop modules that connect abstract ethical theories directly to issues of design, implementation, and technical development.” His research explores how metrics and algorithms shape human values, and he’s published widely on topics like gamification and the ethics of data systems. As a fellow, he wants to launch a cross-listed computing and philosophy course, an AI ethics certificate, and an AI and data ethics center to foster interdisciplinary research.

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Thematic Area: Health Care and Wellness​

Vineet expects to use his training in human-centered design to create AI-powered digital health platforms, such as smartphone-based tools that measure movement and cognitive performance to reduce expert load in clinical assessment and rehabilitation. “I see a massive opportunity to do foundational work bringing together two areas—human-computer interaction and AI—that have diverged over time,” he said. “Responsible AI technologies need human-centered design with multiple stakeholders to be useful in complex situations like health care.”

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Thematic Area: Teaching and Learning

Jihyun Rho examines how people learn from and reason with visual information, and how generative AI is reshaping this visual sense-making. She studies how learners build and revise the structures they use to interpret visual information, and how AI tools shape what learners see, notice, and understand. Her research interests span visual-based learning, data visualization education, and generative AI in education. Before joining the University of Utah, Rho worked as a postdoctoral researcher at the University of Florida. She earned her Ph.D. in learning sciences from the University of Wisconsin–Madison’s Department of Educational Psychology.

Rho joined the University of Utah through the One-U Responsible AI Initiative cluster hire program.

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Thematic Area: Health Care and Wellness

Haoning Xue studies how AI can support healthier and more equitable information environments through conversational AI for health information integrity and decision-making. Her work examines how people use conversational AI to seek health information and identifies disparities in effective AI use. She develops value-aligned conversational systems that encourage health behaviors, such as promoting colonoscopy among women and healthy lifestyles among rural residents. She also investigates how people recognize AI-generated videos and designs literacy interventions that help individuals evaluate online content. “My human-centered AI research aims to strengthen users’ digital health literacy and wellbeing and supports One-U RAI’s commitment to ethical and socially grounded AI,” Xue said. As a fellow, she’ll continue her experiments on human-AI interaction and develop her existing curriculum on AI communication.

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Thematic Area: Health Care and Wellness​

For the last eight years, Yandell has worked almost exclusively on the development of machine learning and AI tools in genomics and population health. A major focus of his work is genetic diagnosis for critically ill newborns. “Responsible AI is the common theme running through all these projects, as health care applications involving AI entail complex ethical and legal responsibilities,” Yandell said.

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Thematic Area: Environment

He Yin is an expert in Earth observation for environmental monitoring. He integrates remote sensing imagery, AI and machine learning, and interdisciplinary approaches to understand environmental change and its consequences for ecosystems and society. His overarching goal is to advance sustainable and just environmental management.

Yin is the principal investigator of projects funded by NASA, the National Science Foundation, Lawrence Livermore National Laboratory, and the Center for International Forestry Research. His research spans armed conflict and its environmental impacts, agricultural land abandonment, natural hazards and disasters, grassland management, and forest monitoring. He also advises United Nations agencies on disaster recovery, reconstruction, and environmental assessment. His recent work on conflict-related environmental impacts has been featured by major media outlets including Al Jazeera, CNN, BBC, The Washington Post, and The Wall Street Journal.

Yin joined the University of Utah through the One-U Responsible AI Initiative cluster hire program.

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Thematic Area: Health Care and Wellness

Faculty Mentors: One-U Responsible AI Initiative faculty fellow Maggie French, Department of Physical Therapy and Athletic Training; Scott Uhlrich, Department of Mechanical Engineering

Gait impairments after stroke are associated with increased fall risk, reduced independence, and diminished quality of life, yet traditional clinical assessments have only moderate associations with these measures and fail to comprehensively measure gait function. Emily Eichenlaub’s work examines how responsible AI can help patients at the bedside. She’ll deploy an affordable, scalable video-based motion capture system to more comprehensively quantify gait impairments for inpatients undergoing post-stroke rehabilitation. The system will use AI-driven pose estimation to provide new insights into patient recovery and inform clinical decision-making.

In May, Eichenlaub earned a Ph.D. from the University of North Carolina and North Carolina State University Lampe Joint Department of Biomedical Engineering. She holds a bachelor's in the same field from the University of Delaware Honors College.

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Thematic Area: Teaching and Learning

Faculty Mentors: One-U RAI faculty fellow Chenglu Li, Department of Educational Psychology; One-U RAI faculty fellow Ana Marasović, School of Computing; Brendan Schuetze, Department of Educational Psychology

Hu is developing an AI-powered tutoring system to make learning algebra more effective and equitable for all middle schoolers. The system uses generative AI to provide personalized support based on each learner’s motivation, understanding, and metacognitive skills—helping struggling students while maintaining transparency and accountability. Crucially, teachers remain in control: every AI-generated instruction includes its pedagogical purpose, so educators can validate and adjust content. “It is time to think beyond the feasibility of AI-powered teaching, on how to use it more effectively and ethically,” Hu said. Hu completed a PhD in cognitive science and psychology from Indiana University Bloomington in May 2025 before working as a research intern at the University of Florida. He aims to create tools that combine cognitive science and AI for responsible, teacher-guided education.

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Thematic Areas: Health Care & Wellness (primary); Environment (secondary)

Faculty Mentors: Bernardo Modenesi, assistant professor, Department of Population Health Sciences; One-U RAI faculty fellow Heather Holmes, associate professor, Department of Chemical Engineering

Kelly is an environmental epidemiologist and spatial data scientist tackling a growing health challenge: how wildfire smoke pollution affects reproductive health. Wildfire smoke contains a mixture of harmful chemicals, and its composition varies depending on what burns—man-made materials can be far more toxic. Kelly is developing a framework using causal AI, which focuses on understanding relationships rather than predicting patterns. By combining advanced modeling with clinician input, the project aims to pinpoint which chemical combinations pose the greatest risks to human health while keeping results transparent and understandable. “This is such an important problem locally and regionally, and One-U RAI is an ideal environment for this research,” said Kelly, who earned her Ph.D. in population health sciences from the U in August 2026 and began her postdoc the following month.

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Thematic Areas: Teaching and Learning (primary); Health Care and Wellness (secondary)

Faculty Mentors: One-U RAI Executive Committee member Sameer Patil, School of Computing; One-U RAI faculty fellow Nina de Lacy, Department of Psychiatry

Khan, a postdoc at Syracuse University, is investigating how generative AI influences autonomy and critical thinking during late adolescence—a pivotal stage for developing independent judgment. As students increasingly use tools like ChatGPT for learning and problem-solving, Khan’s research asks: Does reliance on AI change how young adults make decisions and express original thought? Her project combines behavioral and physiological measures, such as attention and cognitive load, with self-reports to assess ownership of reasoning in AI-assisted tasks. “By linking neuroscientific, behavioral, and institutional analysis, this project contributes a unique evidence base for designing rights-preserving AI and ensuring its adoption enhances rather than erodes human development,” said Khan, who holds a PhD in Informatics from Indiana University Bloomington. Findings will inform education policy and AI regulation.

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Thematic Area: Environment

Faculty Mentors: One-U RAI Executive Committee member Matt Sigman and Jacob Lessard, Department of Chemistry; Taylor Sparks, Department of Materials Science & Engineering

Lampkin’s project aims to address plastic pollution by developing plastics that are “degradable and upcyclable on demand.” He’ll use AI models to accelerate the discovery of special additives that can be built into common, durable plastics—like polystyrene—to safely break them down or transform them into new materials when triggered by light or acid. The project hinges on designing and testing classes of highly reactive chemical compounds and using AI to predict their behavior. To enable the discovery process, Lampkin will create a data-efficient AI algorithm that can identify useful additives more rapidly than conventional trial-and-error experimentation. Data efficiency is crucial because datasets for training AI in many areas of chemistry are sparse due to high experimental costs. “Although this work alone will not solve plastic pollution, it should furnish conceptual and practical advances useful for enhancing the sustainability of plastics,” Lampkin said. “In the short term, my study will generate an innovative AI algorithm that can catalyze molecular discovery campaigns across many domains. In the long term, this project should demonstrate a promising approach for addressing the chemical challenge at the core of the plastic waste crisis.”

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Thematic Area: Health Care and Wellness

Faculty Mentors: Christopher Gregg, Department of Neurobiology; One-U RAI Executive Committee member Aik Choon Tan, Department of Oncological Sciences

Maldonado will build AI models to diagnose depression and anxiety from smartphones and predict treatment outcomes. Mental health is a priority for Utah, which ranks 11th in the country for adults with mental illness and 4th for adults with serious suicidal ideation, yet faces a shortage of providers. “My project has the potential to transform the diagnosis and treatment of mental health disorders across different fields of medical care, offering scalable, equitable, and impactful solutions for diverse populations,” Maldonado said. He’ll work with experts from psychiatry, oncology, and more to develop models using already-acquired data—including patient assessment videos from Storyline Health Behavioral AI, an app co-created by his advisor, Christopher Gregg. Maldonado’s user-facing tool will be available via Storyline Health and the models will be open source, encouraging accessibility and further collaboration at the U and beyond.

Maldonado holds a Ph.D. in neuroscience and a master’s in biomedical informatics, both from the University of Utah. He has worked as a postdoctoral fellow in Gregg’s lab since 2023 and also served as a postdoc under Julio Facelli from 2023 to 2024. His long-term goal is to lead his own lab focused on applying AI to solve critical challenges in health care and precision medicine. “I am particularly passionate about developing scalable, ethical, and innovative AI solutions that bridge the gap between computational biology and clinical applications,” he said, “ultimately improving patient outcomes.”

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Thematic Areas: Health Care and Wellness; Teaching and Learning

Faculty Mentors: One-U RAI Faculty Engagement Committee member Jeff Phillips and Vivek Srikumar, School of Computing; Zac Imel, Department of Educational Psychology

AI tools have the potential to improve mental health on a global scale—especially if tools can be leveraged across many languages. Schou, who is Danish, will use text and video data from online therapy in his home country to study how AI models originally trained in English can be adapted to a less-common language without erasing nuance. “Danish is an ideal gateway for studying how to adapt AI models to underrepresented linguistic and cultural contexts: it is underrepresented in large models, yet supported by a growing national AI infrastructure,” Schou said, citing national investments such as Gefion, one of the most powerful supercomputers in the world. All data will remain in Denmark and be used only with informed consent. Schou will use AI-driven algorithms to responsibly support therapists in crafting therapeutic messages and detecting early signs of patient disengagement, without compromising clinical intent. The same models could also be used as learning tools in supervised training environments, supporting AI-powered instruction for mental health professionals. “By adapting these tools to low-resource languages, the project also promotes broader access and inclusion in therapist education,” Schou said.

The University of Utah, Schou said, offers an “ideal environment” for his proposed project because of its leading researchers in natural language processing, psychotherapy-AI integration, and data science.

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Thematic Area: Health Care and Wellness

Faculty Mentors: Chris Hill, Department of Biochemistry; Chris Miles, Department of Mathematics

Most modern medicines work by targeting proteins in the body. However, major challenges exist in identifying which proteins to target for a given disease, and where on the protein a drug should attach for maximum effectiveness. Jeff Swan is tackling this bottleneck using specialized AI models that treat proteins’ genetic sequences as a language, decoding how they translate into biological function. Through his research, he will develop methods to extract the AI’s internal decision-making processes and use them to identify the chemical structures within proteins that make the most valuable targets for pharmaceutical intervention. This strategy will then be applied to a broad range of potential drug targets, providing proof-of-concept and paving the way for new therapeutic discoveries. Ultimately, Swan’s research aims to streamline drug development, offering hope to patients who currently lack effective treatment options.

Swan has worked in the laboratory of Chris Hill since 2024 as a Jane Coffins Childs Postdoctoral Fellow. He holds a Ph.D. in chemistry from the University of California Santa Cruz, following a master's in chemistry from the University of Colorado Boulder, and a bachelor's in biochemistry and molecular biology from Michigan State University.

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Thematic Area: Health Care and Wellness

Faculty Mentors: Jacob George, Department of Electrical & Computer Engineering and Department of Physical Medicine & Rehabilitation; Daniel Brown, School of Computing

Trout is advancing neurotechnology to improve life for people with limb loss. His recent work on an AI-powered bionic hand was published in Nature Communications and featured by NPR and KSL TV. Trout’s research centers on AI-driven neural decoders—algorithms that translate nerve signals into movement commands. Patients can provide only limited data, so Trout develops data-efficient, patient-specific AI frameworks that learn from sparse signals and reflect user preferences, such as prioritizing stability or speed. He aims to make neuroprostheses more intuitive and customizable while setting ethical standards for data use. “This work will provide a means to study the function of AI, how it’s used by patients, and its long-term personal and medical impacts,” he said. Trout earned a PhD in electrical and computer engineering from the U in August 2025 under Jacob George and has continued as George’s postdoc.

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Thematic Area: Environment Faculty Mentors: One-U RAI faculty fellow Brian Codding, Department of Anthropology; One-U RAI Executive Committee member Simon Brewer, Department of Geography Vernon will build an AI hydrological model and open-source tools that estimate soil moisture and runoff potential, ultimately aiding efforts like sustainable development. “While a great deal of work is being done in AI research to understand the consequences of climate change for hydrological systems, the complexity of the models makes them extremely hard to implement and interpret,” Vernon said. “This project seeks to overcome those challenges." Read the original announcement.

Thematic Area: Environment

Faculty Mentors: One-U RAI Faculty Engagement Committee member Divya Chandrasekhar, Department of City & Metropolitan Planning; Tom Cova, School of the Environment, Society & Sustainability; Tolga Tasdizen, Department of Electrical and Computer Engineering; Marina Kogan, School of Computing

As climate-related hazards become more frequent and severe, people leading recovery efforts need to make informed decisions long after the emergency itself. Southern California and Western North Carolina, for example, continue to rebuild months after the Palisades Fire and Hurricane Helene, respectively. While AI research has largely focused on immediate response, post-disaster recovery—key to long-term community resilience—remains understudied. Wang’s project will bridge this gap by developing AI methods to analyze diverse data sources. Specifically, he will integrate social media data, geolocated imagery, mobility data, field observations, and official disaster reports to understand how communities navigate the complex and extended phases of recovery. He’ll identify major recovery benchmarks and disparities in aid distribution across communities. “With mentorship from faculty members in disaster recovery, computer vision, and crisis informatics, this project brings together advanced analytical approaches and practical insight to ensure the research maintains methodological integrity while addressing real-world recovery challenges,” Wang said. “My long-term goal is to build AI systems that respond to the evolving needs and challenges in disaster response and recovery—helping communities make informed decisions, meet changing needs, and rebuild more equitably.”

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