Xiaojun (Jenny) Yuan, Ph.D., is an Associate Professor in the College of Emergency Preparedness, Homeland Security, and Cybersecurity at the University at Albany, State University of New York. Her research interests include both Human Computer Interaction and Information Retrieval, with the focus on user interface design and evaluation and human information behavior. 

She has received various grants and contracts, including from the Institute of Museum and Library Services, SUNY seed grant, Initiatives For Women Program at University at Albany, and New York State Education Department. 

She published extensively in journals in information retrieval and human computer interaction (including the JASIS&T, IP&M, Journal of Documentation, etc.), and conferences in computer science and information science (ACM SIGIR, ACM SIGCHI, ACM CHIIR, ASIS&T, etc.).

Dr. Yuan received her Ph.D. from Rutgers University at School of Communication and Information, and Ph.D. from Chinese Academy of Sciences in Institute of Computing Technology. She received her M.S. in Statistics from Rutgers University and M.E. and B.E. in Computer Application from Xi’an University of Science & Technology in China. She serves as committee members and reviewers in various professional conferences such as ASIS&T, iConference, ACM SIGIR, ACM SIGCHI, ACM CHIIR, and ChineseCHI. She serves an Editorial Board member of Aslib Journal of Information Management (AJIM), an Editorial Board member of The Annual Review of Information Science and Technology (ARIST) and a Board member of the International Chinese Association of Human Computer Interaction. She is a member of the Association for Information Science and Technology (ASIS&T), Association for Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE).

• Yuan, X., Wu, D., & Gayle, D. B. (Eds.). (2022). Social Vulnerability to COVID-19: Impacts of Technology Adoption and Information Behavior. Springer. 
• Gayle, D. M. B., & Yuan, X. J. (2023). Empowered or Left Behind: Use of Technology During COVID-19. Taylor and Francis.
• Sa, N., & Yuan, X. (2022). Improving the effectiveness of voice search systems through partial query modification. Journal of the Association for Information Science and Technology, 73(8), 1092-1105.
• Xing, Z., Yuan, X., & Mostafa, J. (2022, March). Age-related Difference in Conversational Search Behavior: Preliminary Findings. In ACM SIGIR Conference on Human Information Interaction and Retrieval (pp. 259-265). 
• Bennett Gayle, D., Yuan, X., & Knight, T. (2021). The coronavirus pandemic: Accessible technology for education, employment, and livelihoods. Assistive Technology, 1-8.