Rate My Professor Lingyao Li

Lingyao Li is an Assistant Professor in the School of Information at the University of South Florida, a position she has held since 2024. Prior to this, she conducted postdoctoral research at the School of Information at the University of Michigan from 2022 to 2024, working with Dr. Libby Hemphill, and briefly at the Department of Civil and Environmental Engineering at the University of Maryland in 2022. She earned her Ph.D. in Civil and Environmental Engineering from the University of Maryland, College Park, advised by Dr. Gregory Baecher and co-advised by Dr. Michelle Bensi. Li also holds an M.S. and B.S. in Naval Architecture and Ocean Engineering from Harbin Engineering University, along with a minor in Business Administration. During her doctoral studies, she completed 25 courses across civil engineering, statistics, information science, and computer science, developing a strong foundation in human-centered data science that utilizes crowdsourced data and natural language processing techniques. She collaborated closely with Dr. Yongfeng Zhang from Rutgers University and spent additional time at Michigan to advance her expertise in computational social science, social computing, and AI studies.

Li's research centers on natural language processing, large language models, social networks, and crowdsourcing to address socio-technical challenges in urban informatics and health informatics, promoting AI for social good. Her work explores resilient and equitable communities, public opinions on health interventions, LLM-driven multi-agent systems, chatbots, and the reasoning capabilities, trustworthiness, and societal impacts of large language models. Key publications include "NPHardEval: Dynamic benchmark on reasoning ability of large language models via complexity classes" (ACL 2024, with L. Fan et al.), "Landscape of large language models in global English news: Topics, sentiments, and spatiotemporal analysis" (AAAI ICWSM 2024, with L. Xian et al.), "'HOT' ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social media" (ACM Transactions on the Web, 2023, with L. Fan et al.), "Crowdsourced reviews reveal substantial disparities in public perceptions of parking" (arXiv:2407.05104, 2024), "Exploring the potential of social media crowdsourcing for post-earthquake damage assessment" (International Journal of Disaster Risk Reduction, 2023), and "Dynamic assessment of the COVID-19 vaccine acceptance leveraging social media data" (Journal of Biomedical Informatics, 2022). Her contributions have appeared in venues such as Sustainable Cities and Society, Fire Safety Journal, and AGU Fall Meeting presentations.