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Chengyuan Yao
Email /
Google Scholar /
LinkedIn /
Twitter
I am currently a Ph.D. candidate in
Measurement, Evaluation, and Statistics
at
Teachers College, Columbia University
in New York City, where I am fortunate to be advised by
Dr. Renzhe Yu
and am a member of the
AEQUITAS Lab.
Previously, I earned a B.A. in Applied Mathematics with Minors in Data Science and Education from
UC Berkeley.
Research: My research lies at the intersection of Responsible AI and Educational Data Science, examining how AI methods can be responsibly developed and applied in real-world contexts. I am currently exploring and interested in the following topics:
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Trustworthy Transfer Learning: Examining challenges of algorithmic fairness and data privacy in transfer learning, aiming to democratize access to trustworthy educational models, especially in under-resourced educational contexts.
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Measurement and Evaluation for Large Language Models: Advancing more reliable and theoretically grounded evaluation methods for large language models (LLMs), with a focus on construct validity, consistency across tasks, and alignment with real-world goals.
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News
💼 May. 2026: I am joining Microsoft AI as an Applied Scientist Intern this summer.
📣 April. 2025: I was awarded the Provost's Grant for Conference Presentation and Professional Development.
⭐ March. 2025: "Towards Fair and Privacy-Aware Transfer Learning for Educational Predictive Modeling" received the Best Full Paper Award at LAK2025.
🎉August. 2023: I was awarded the Doctoral Research Fellowship to support my Ph.D. research.
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From Leaderboards to Decisions: A Psychometric Perspective on Criterion-Referenced Evaluation of Large Language Models
Chengyuan Yao, Zhen Xu, Jiayu Zheng, Renzhe Yu
LAK '26 LLM Psychometrics Workshop
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Who's More Biased? Calibrating LLM Generation Against Human Responses in Postsecondary Online Discussion Forums
Daniel March, Zhen Xu, Chengyuan Yao, Renzhe Yu
L@S 2026
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Are Online Discussion Forums Falling Behind in the Age of AI? Preliminary Evidence from Students’ Cognitive and Social Engagement Shifts in 370,000+ Posts
Zhen Xu, Yijun Dai, Chenxi Shi, Siyan Li, Chengyuan Yao, Renzhe Yu
L@S 2026
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When the Past Misleads: Rethinking Training Data Expansion Under Temporal Distribution Shifts
Chengyuan Yao, Yunxuan Tang, Christopher Brooks, Rene Kizilcec, Renzhe Yu,
AIES 2025
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Understanding Predictive Models of Student Success with a Multiverse Analysis
Yunxuan Tang, Emma Harvey, Chengyuan Yao, Renzhe Yu, Rene Kizilcec and Christopher Brooks,
EDM 2025
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Towards Fair and Privacy-Aware Transfer Learning for Educational Predictive Modeling
Chengyuan Yao,
Carmen Cortez, Renzhe Yu
🏆 Best Full Research Paper Award
LAK 2025
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Technology-Based Instructional Strategies Show Promise in Improving Self-Regulated Learning Skills at Broad-Access Postsecondary Institutions
Renzhe Yu, Hui Yang, Xiaoying Lin, Chengyuan Yao, Paul Burkander, Krystal Thomas, Jessica Mislevy
L@S 2024
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Co-Organizer, Fair4AIED 2026
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Program Committee Member, AIED 2026
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Program Committee Member, AIES 2025
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Reviewer, FAccT 2026
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Reviewer, L@S 2025
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Reviewer, AIES 2024
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Student Volunteer, alt-FAccT 2025
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Co-Host, EAAMO NYC Meetup 2025
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Student Representatives, Student Conduct Committee, Teachers College, Columbia University 2025-2027
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E-board Member, Data Science and Education Association, Teachers College, Columbia University 2023-2024
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TEDx Organizer, TEDxYouth@YouyiWRoad 2017
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Guest Lecturer, HUDK 4051 Learning Analytics: Process and Theory, Spring 2026
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Course Assistant, HUDM 4122 Probability and Statistical Inference, Summer 2025
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Course Assistant, HUDK5053 Learning Analytics Practicum, Summer 2025
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Course Assistant, HUDK5053 Feature Engineering Studio, Summer 2024
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Course Assistant, HUDM5122 Applied Regression Analysis, Spring 2024
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Last Updated: May 2026.
Website template by Jon Barron.
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