Rate My Professor Hong Huang

Dr. Hong Huang is an Associate Professor in the School of Information within the College of Arts and Sciences at the University of South Florida. His multidisciplinary academic background includes a B.S. degree in Biochemistry from Zhongshan (Sun Yat-sen) University in Guangzhou, China, an M.S. in Genetics from Florida A&M University, an M.S. in Computer Science from Florida State University, and a Ph.D. in Information from Florida State University. This foundation in biological sciences, computer science, and information science enables him to bridge information and library science, bioinformatics, and information and learning technology.

Huang's research specializations include data management and practice with a focus on socio-cultural and curation issues, AI/ML data practice and sharing, IT applications in library and education, bio/health information and learning, bioinformatics, and information and learning technology. He has served as Principal Investigator or Co-Principal Investigator on collaborative and federal grant awards, including from the USDA, in areas such as data management and practice and IT in learning science. With over 140 peer-reviewed publications and conference presentations, his influential works encompass topics like genomic data curation, health information-seeking behaviors, crowdfunding success prediction, and livestreamed learning motivations. Key publications include "Assessing the importance of content versus design for successful crowdfunding of health education games: online survey study" (JMIR Serious Games, 2024, with H. Yu and W. Li); "What remains now that the fear has passed: Developmental Trajectory Analysis of COVID-19 Pandemic for co-occurrences of Twitter, Google Trends, and Public Health Data" (Disaster Medicine and Public Health Preparedness, 2023, with B. Rathke and Y. Han); "Metadata functional requirements for genomic data practice and curation" (Information Research, 2023, with J. Qin); "Entrepreneurship success: predicting crowdfunding campaigns using model-based machine learning methods" (International Journal of Crowd Science, 2022, with M. Oduro and H. Yu); and "Exploring the motivation of livestreamed users in learning computer programming and coding" (The Electronic Journal of e-Learning, 2021, with Y. Li). Huang contributes editorially as Associate Editor for the Journal of Information and Learning Sciences (Emerald) and Editorial Board Member for Library & Information Science Research (Elsevier).