artificial intelligence for the public’s health

Researchers in the College of Public Health and Health Professions are using artificial intelligence tools to improve population health and treatment interventions.

research themes

Applied AI

Studies led by faculty in both public health and health professions disciplines explore real-world health issues, including the outcomes of pharmaceutical treatments in large populations, the effects of re-purposing drugs for other health conditions, the impact of environmental contaminants on the risk of diseases, such as cancer, and the use of assistive technology to improve daily life for older adults and people with disabilities.

Ethical AI

Scientists are developing fair and equitable models that not only recognize social bias and health disparity, but also can be acted upon in interventions. Examples include increasing access to care for vulnerable and underserved populations and reducing stigma in order to improve quality of life for people living with HIV.

Interdisciplinary AI

Research across disciplines includes fusing molecular epidemiology and deep learning methods to track and curb transmission of infectious diseases, as well as AI-empowered neurocognitive research.  

Methodological AI

Methodological approaches include advancements in machine learning and “causal AI” with strong biostatistical foundations, such as efficient multi-omics big data analysis, deep propensity networks, automated learning of causal effects from large-scale electronic health records, multi-site large clinical trials, and Bayesian dynamic trials.

new hire


Zhoumeng Lin, BMed, PhD, DABT, CPH

Dr. Lin’s research focuses on the development and application of computational technologies to address research questions related to nanomedicine, animal-derived food safety assessment, and environmental chemical risk assessment. The long-term goal is to develop AI-assisted computational approaches to support decision-making in human, animal and environmental health.

Dr. Lin joined the PHHP department of environmental and global health this summer as the first faculty member in the college hired under UF's AI initiative

Featured projects

Predicting HIV transmission patterns

Dr. Mattia Prosperi and colleagues are using an AI technique known as deep learning to study patterns of HIV transmission. Deep learning methods use artificial neural networks that learn from complex data sets. The researchers plan to identify social, demographic and behavioral risk profiles that will enable more powerful predictions about future trends, including where HIV transmission clusters are likely to occur.

red ribbon

Preventing dementia

Dr. Adam Woods studies the use of non-invasive transcranial direct current stimulation for improving brain health among older adults. With support from a new grant, Woods and his team are using neuroimaging-derived computational modeling and artificial intelligence-based machine learning methods to better understand the mechanisms of treatment response and to develop precise individualized models for dosing.

Adam Woods with older adult



The college has created three new undergraduate courses that can be taken as part of UF’s campus-wide certificate program, AI Fundamentals and Applications, or as part of a PHHP-specific certificate program that will be submitted to the UF Curriculum Committee in Fall 2021. The three courses are “Higher Thinking for Healthy Humans: AI in Healthcare and Public Health,” “Ethics in AI: Who’s Protecting Our Health” and “Data Visualization in the Health Sciences.”


The college has begun developing a certificate in Artificial Intelligence Research Methodologies in Healthcare and Public Health for graduate students that that will focus on using AI to answer health-related research questions. Once these are fully established, the courses will be developed and submitted to the Graduate Council for approval.


Researchers use AI to develop precision dosing for treatment aimed at preventing dementia

An MRI-derived model of electric current flow in an individual’s brain. Red and blue outlines represent the size and position of electrodes placed on the scalp to deliver transcranial direct current stimulation to the brain. Electrical current is injected at the location of the red outline and returned at the location of the blue outline during stimulation.

more information


For more information on AI activities at PHHP, contact the college’s coordinator for AI, Dr. Mattia Prosperi.

Diversity, Equity and Inclusion

The college is committed to creating an inclusive environment where everyone is respected and valued.

AI at UF Health

UF Health is creating an academic hub to advance AI in the health sciences grounded in the values of community, trustworthiness, and diversity, equity and inclusion.

AI AT The university of florida

AI leadership for the future

The university is becoming a worldwide leader in AI workforce development with an AI-across-the-curriculum approach that infuses AI and data science into all academic endeavors. UF’s $100 million investment in AI will transform Florida’s workforce and economy to resonate globally and continue the university’s rise into America’s top-tier public universities.

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