People

Hong Huang

Associate Professor

CONTACT

Office: CIS 2040
Email

BIO

Dr. Hong Huang is an Associate Professor in the School of Information at University of South Florida. He received a B.S. degree in Biochemistry, both M.S. degrees in Genetics and Computer Science, and a Ph.D. in Information from the Florida State University. His research and teaching areas encapsulate three related disciplines- information and library science, bioinformatics, and information & learning technology. With his extensive LIS, bioinformatics backgrounds and work experiences, he bridges these disciplines in various ways. His research interests include AI and large language models in information practice, research data management and sharing, human–AI interaction in libraries and education, and health and biomedical information behavior, with related work on learning and edutainment. He has published 140 peer review publications and conference presentations. He is the PIs or Co-PIs with collaborative and federal grant awards (e.g., USDA) in data management & practice, and IT in learning science. He has served as the Associated Editor for Journal of Information and Learning Sciences (Emerald), the Editorial Board Member for Library & Information Science Research (Elsevier).

EDUCATION

  • Ph.D., Florida State University
  • M.S., Florida State University
  • M.S., Florida A&M University
  • B.S., Zhongshan (Sun Yetsen) University

Recent Publications & Research

  • Huang H., Yu H., Li W. (2024). Assessing the importance of content versus design for successful crowdfunding of health education games: online survey study. JMIR Serious Game (DOI:10.2196/39587). 
  • Rathke, B. Han Y. Huang H. (2023). What remains now that the fear has passed: Developmental Trajectory Analysis of COVID-19 Pandemic for co-occurances of Twitter, Google Trends, and Public Health Data, Disaster Medicine and Public Health Prepardness, (DOI:10.1017/dmp.2023.101).
  • Huang, H., Qin J. (2023). Metadata functional requirements for genomic data practice and curation. Information Research, (In press).
  • Oduro M., Yu H., Huang H. (2022) Entrepreneurship success: predicting crowdfunding campaigns using model-based machine learning methods. International Journal of Crowd Science, 6(1), 7-16. IEEE.org. (DOI:10.26599/IJCS.2022.9100003).
  • Huang H., Li Y. (2021). Exploring the motivation of livestreamed users in learning computer programming and coding. The Electronic Journal of e-Learning, 19(5), 363-375. (DOI:10.34190/ejel.19.5.2470).