I am an Assistant Professor in the Human-Computer Interaction Institute at Carnegie Mellon University, where I direct the CARE (Collective AI Research and Evaluation) Lab. I am also part of the CMU-NIST Cooperative Research Center on AI Measurement Science & Engineering (AIMSEC). I received my PhD from the University of Illinois at Urbana-Champaign.

I'm an interdisciplinary scholar situated at the intersection of human-computer interaction, artificial Intelligence, and public policy. Broadly, I study the social, ethical and policy implications of digital platforms and algorithmic systems. My work has been generously supported by the National Science Foundation, Amazon Research, Cisco Research, Google Research, Microsoft Research, Open Philanthropy, The Public Interest Technology University Network, Block Center for Technology and Society, CyLab, and more.

A complete list of my publications can be found on my Google Scholar page.

• 08/2026: Congratulations to our postdoctoral researcher Chelsea Wang, who will join the UC Berkeley School of Education as an Assistant Professor in Janurary 2027!

• 08/2026: We received a grant from the National Science Foundation to understand, detect, and mitigate social-relational harms in human-AI interactions (with Jodi Forlizzi, Maarten Sap, and Chelsea Wang).

• 05/2026: We received two Microsoft Research AI and the New Future of Work awards for the projects "TeamCompass: AI Facilitation for Collective Intelligence" (with Laura Dabbish and Alice Qian) and "TeamFlow: AI Facilitators for Attention Curation in Team Collaboration" (with Hancheng Cao and Qing Xiao).

• 03/2026: Our paper, Large Language Models in Peer-Run Community Behavioral Health Services received a Best Paper Honorable Mention 🎖 at CHI 2026.

• 03/2026: Our paper, The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models received a Best Paper Honorable Mention 🎖 at CHI 2026.

• 07/2025: We received a grant from the National Science Foundation to advance participatory and community-centered AI design methods with peer-run safety-net behavioral health services.

• 12/2024: Our paper PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals has received a Best Paper Award 🏆 at NeurIPS GenAI for Health Workshop 2024!

• 10/2024: Our paper Investigating What Factors Influence Users’ Rating of Harmful Algorithmic Bias and Discrimination has received a Best Paper Award 🏆 at HCOMP’24!

• 10/2024: We received a planning grant from the National Science Foundation to explore participatory AI design opportunities with peer-run mental health organizations.

• 05/2024: We received a grant from Open Philanthropy to build a database and taxonomy of real-world LLM use cases.

• 04/2024: We received the 2024 Google Research Scholar Award in Human-Computer Interaction.

• 02/2024: Hong was selected as a Microsoft Research AI & Society Fellow to work on "Supporting the Responsible AI Red-Teaming Human Infrastructure".

• 09/2023: We received a grant from The Public Interest Technology University Network to develop a community-centered toolkit for advancing critical AI literacy.

• 04/2023: Our paper Understanding Frontline Workers’ and Unhoused Populations’ Perspectives on AI Used in Homeless Services has received a Best Paper Award (top 1% of submissions) 🏆 at CHI'23!