UNF graduate student uses artificial intelligence to combat nutritional misinformation

As social media becomes a common source of health information, distinguishing fact from fiction has never been more urgent. At the University of North Florida, graduate student Vishwaa Shah is using artificial intelligence to help address that challenge. 

After earning her undergraduate degree in data science at UNF, Shah continued into the Master of Science in Computer and Information Sciences program in 2025 determined to deepen her expertise in AI and apply it to meaningful research. 

“I wanted to explore how data science could be used in innovative, real-world contexts,” Shah said. “UNF offered the hands-on research opportunities and faculty mentorship I was looking for.” 

Her thesis focuses on detecting nutritional misinformation on social media using large language models. The project integrates sentiment analysis, linguistic and affective features, and advanced natural language processing techniques to better understand how health claims are framed and shared online. 

What makes the research especially impactful is its interdisciplinary approach. Shah works closely with nutrition experts to ensure the models are grounded in accurate, real-world context. 

“Collaborating with faculty outside of computer science strengthened the research tremendously,” she said. “It helped us think critically about both the technical and public health implications.” 

Her research has already led to multiple research submissions and presentations at the national and international levels, including recognition at the UNF School of Computing Symposium. Shah is a joint first author on a paper accepted to SemEval 2026 and first author on two additional papers accepted to the Linguistic Annotation Workshop and BioNLP 2026 Workshop, all hosted alongside with the Association for Computational Linguistics 2026. She is also the first author of an abstract accepted to the 2026 Mobilizing Computable Biomedical Knowledge North America Chapter meeting that will be published in the Learning Health Systems journal.

“This level of research productivity is virtually unheard of for a master’s student in our School of Computing — it speaks to Vishwaa’s work ethic, curiosity and ability to lead meaningful, real-world research,” said Dr. Indika Kahanda, associate professor in the UNF School of Computing who served as Shah's thesis committee chair. 

Through the process, Shah has developed advanced skills in research design, academic writing and technical problem-solving, while also gaining experience presenting her work in academic settings. 

Beyond research, those skills have translated directly into professional experience. Shah recently completed an AI engineering internship, where she applied machine learning and natural language processing techniques developed through her graduate work. 

As Shah prepares to graduate in 2027, she plans to pursue a career in AI engineering focused on socially responsible applications of machine learning.   

“The program gave me both the technical foundation and the confidence to take on real-world problems,” Shah said.