Julia Hsin-Ping Hsu
I am a Ph.D. Candidate in Information Technology with a concentration in Information Sciences and Technology at the School of Computing, George Mason University. My research focuses on Computational Social Sciences and Information Sciences, where I apply data-driven and computational methods to study social phenomena and improve information access. My broader interests include Computational Social Sciences, AI for social good, Community Informatics, Civic Technology, and Health Informatics.
I am currently a Graduate Research Assistant working with Dr. Myeong Lee at the Community Informatics Lab, where I collaborate on projects that leverage computational approaches to address societal challenges.
News & Events
- [Jan. 2026] Thrilled to share that I successfully defended my doctoral dissertation!
- [Nov. 2025] Presented my paper “From Open-Ended Text to Taxonomy: An LLM-Based Framework for Information Sources for Disability Services” at ASI&ST 2025!
- [Nov. 2025] Participated in AI in Public Sector and Doctor Colloquium at ASI&ST 2025.
- [Nov. 2025 ] Grateful for receiving the Doctoral Dissertation Completion Grant from the Provost’s Office!
- [Sep. 2025] Presented our poster “An AI-Based Framework for Understanding Occupational Injuries across Virginia” at the Virginia Academy of Science, Engineering and Medicine (VASEM) Summit on Artificial Intelligence.
- [Sep. 2025] My poster for SAFETI (Strategic Analysis for Fine-granular Injury and Fatality PrEvenTion Insight) project was awarded 3rd place in the poster session at the Converge AI: Government Solutions Forum hosted by AI in Gov.
- [June 2025] Passed my dissertation proposal!
- [May 2025] Attended the 2025 Consortium for the Science of Sociotechnical Systems (CSST).
Recent Publications
- Disability Misinformation on Facebook: A Comparison of LLM-based Fact-Checking Tools (in iConference 2026).
- Predicting the success of local gatherings: A comparison of organizer- and participant-side success in Meetup (in Cities 2026).
- From Open‑Ended Text to Taxonomy: An LLM‑based Framework for Information Sources for Disability Services (in ASIST 2025).
- Leveling Socioeconomic Disparities: The Role of Service Availability in School Dropout Rates (in Social Work Research 2025)
