Katelyn Xiaoying Mei
Ph.D. Candidate
University of Washington
I'm a fourth-year PhD candidate in Information Science at the University of Washington. I'm fortunate to be advised by Lucy Lu Wang and Katharina Reinecke. I'm also very grateful to be mentored by Allison Koenecke and Mona Sloane . Before my PhD, I spent four amazing years at Middlebury College from which I obtained my Bachelor's of Art in Psychology and Mathematics.
My research interests derive from the intersection of psychology, humanties, and data science. Through large-scale online experiments and collection of real-world social media data, my projects focus on human cognition and decision-making in the age of generative AI, including 1) how individuals interact with AI systems in various settings, 2) how AI systems affect individuals' behaviors, and 3) psychological factors underlying our engagement with AI systems.
News
May 2026
Paper Presentation at ICWSM 2026!
I presented our work on characterizing the roles and uses of Grok on X at ICWSM 2026!
April 2026
Paper accepted at ACL 2026!
Our work on human evaluation protocols for long-form text generation has been accepted at ACL 2026 for oral presentation! I'll be attending ACL 2026 in San Diego, CA. Looking forward to seeing everyone there!
Education
University of Washington
Ph.D. in Information Science
Advisor: Prof. Lucy Lu Wang and Prof. Katharina Reinecke
Middlebury College
B.A. in Psychology and Mathematics
Publications
The International AAAI Conference on Web and Social Media 2026
Grok in the Wild: Characterizing the Roles and Uses of Large Language Models on Social Media
Katelyn X. Mei, Robert Wolfe, Nicholas Weber, Martin Saveski
Characterize the roles and uses of Grok on X.
The 64th Annual Meeting of the Association for Computational Linguistics (ACL) 2026
Illusions of the Gold Standard: A Large-scale Analysis of Human Evaluation Protocols for Long-form Text Generation
Katelyn X. Mei, Yili Hsu, Minjoon Choi, Zongwan Cao, Chenjun Xu, Bingbing Wen, Su Lin Blodgett, Lucy Lu Wang
Large-scale analysis of human evaluation protocols for long-form text generation.
ACM Workshop on Human-AI Interaction for Augmented Reasoning (CHI) 2025
Designing AI Systems that Augment Human Performed vs. Demonstrated Critical Thinking
Katelyn X. Mei, Nic Weber
Propose new definitions for evaluating the impact of GenAI on human critical thinking and systems design.
ACM Conference on Fairness, Accountability, and Transparency (FAccT) 2026
Addressing Pitfalls in Auditing Practices of Automatic Speech Recognition Technologies: A Case Study of People with Aphasia
Katelyn X. Mei, Anna Seo Gyeong Choi, Hilke Schellmann, Mona Sloane, Allison Koenecke
Propose new practices for auditing ASR systems to better include people with speech impairments.
ACM Transactions on Computer-Human Interaction (TOCHI) 2025
Passing the Buck to AI: How Individuals' Decision-Making Patterns Affect Reliance on AI
Katelyn X. Mei, Rock Yuren Pang, Alex Lyford, Lucy Lu Wang, Katharina Reinecke
Examine the effect of individuals' decision-making patterns on their reliance on AI suggestions.