People

Hong Huang

Associate Professor

CONTACT

Office: CIS 2040
Email

CV

BIO

Dr. Hong Huang is an Associate Professor in the School of Information at the University Â鶹ÊÓƵ. He received a B.S. degree in Biochemistry, both M.S. degrees in Genetics and Computer Science, and a Ph.D. in Information from 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/genetics backgrounds and work experiences, he bridges these disciplines in various ways. His research interests include data management, AI/ML data practice and sharing, IT in library and education, as well as bio/health information and learning. He published 140 peer review publicaitons 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 served as the Associated Editor for Journal of Information and Learning Sciences (Emerald), the Editorial Board Member 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).