This fall the University of Florida reached its goal of ranking in the top 5 among public universities, according to the latest U.S. News & World Report rankings of the nation’s best colleges. While many factors played a role in that impressive achievement, no doubt the university’s substantial investment in artificial intelligence research, education and workforce development is reflected in UF’s rise.
At the core of UF’s AI capabilities is HiPerGator, the third most powerful computer among educational institutions in the world and the eighth most powerful computer in the U.S.
The university’s investment in AI also provides a unique opportunity for students. UF is the first university in the country to integrate AI across the university’s entire curriculum, positioning our students to apply AI skills once they enter the workforce. At PHHP, we are preparing students to understand AI fundamentals, ethical implications and how AI can be used to understand or predict health outcomes as well as better serve underserved populations. We have created three new courses for undergraduate students and expect to launch them within the coming year.
In addition, with a recent $20 million-a-year allocation from the Florida Legislature, UF is recruiting 100 faculty members to add to the existing AI expertise among our faculty. In this issue you’ll meet our newest faculty hires with AI expertise. We intend to recruit more faculty to PHHP under the AI initiative as well as develop AI research hubs in order to foster collaboration and create new synergies.
Within PHHP, AI research projects range from developing algorithms that underpin AI models to developing applications that address a range of different health problems, including food safety, treatment response predictions, and reliable and valid AI models that don’t disadvantage certain populations. Research in the college broadly falls under four themes:
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 repurposing 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.
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.
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 approaches include advancements in machine learning and “causal AI” with strong biostatistical foundations.
UF’s computing power and expanded expertise are opening up new possibilities for our faculty and students that did not exist even a decade ago. If used appropriately, AI technology has the capability to address health disparities while rapidly advancing precision medicine, new treatments, disease surveillance, and much more. It will be exciting to see where AI technology can take us in the next decade.