I am a first-year Ph.D. student in the Department of Computer Science and Engineering at Michigan State University, advised by Dr. Jiliang Tang. I received my B.A. in Economics and Mathematics and B.S. in Computer Science degrees both from Columbia University, where I built a foundation that bridges technical expertise with humanistic perspectives. My research focuses on the intersection of large language models (LLMs) and education, particularly automated assessment, fairness, and human-centered AI. I am especially interested in developing multi-agent LLM frameworks for tasks such as grading, bias detection, and supporting teacher professional development, with the goal of creating systems that are both effective and socially impactful.

📝 Publications

• A llm-driven multi-agent systems for professional development of mathematics teachers, Kaiqi Yang, Hang Li, Yucheng Chu, Ahreum Han, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu, arXiv 2025

• LLM-based Automated Grading with Human-in-the-Loop, Hang Li, Yucheng Chu, Kaiqi Yang, Yasemin Copur-Gencturk, Jiliang Tang, arXiv 2025

• Enhancing LLM-Based Short Answer Grading with Retrieval-Augmented Generation, Yucheng Chu, Peng He, Hang Li, Haoyu Han, Kaiqi Yang, Yu Xue, Tingting Li, Joseph Krajcik, Jiliang Tang, in Proceedings of the 18th International Conference on Educational Data Mining (EDM), 2025

• Bringing Generative Artificial Intelligence (GenAI) to Education, Hang Li, Kaiqi Yang, Yucheng Chu, Jiliang Tang, in Proceedings of the 18th International Conference on Educational Data Mining (EDM), 2025

• Ask-before-detection: Identifying and mitigating conformity bias in llm-powered error detector for math word problem solutions, Hang Li, Tianlong Xu, Kaiqi Yang, Yucheng Chu, Yanling Chen, Yichi Song, Qingsong Wen, Hui Liu, arXiv 2024

• Unpacking political bias in large language models: Insights across topic polarization, Kaiqi Yang, Hang Li, Yucheng Chu, Yuping Lin, Tai-Quan Peng, Hui Liu, arXiv 2024

• Beyond Partisan Leaning: A Comparative Analysis of Political Bias in Large Language Models, Tai-Quan Peng, Kaiqi Yang, Sanguk Lee, Hang Li, Yucheng Chu, Yuping Lin, Hui Liu, arXiv 2024

• A LLM-powered automatic grading framework with human-level guidelines optimization, Yucheng Chu, Hang Li, Kaiqi Yang, Harry Shomer, Hui Liu, Yasemin Copur-Gencturk, Jiliang Tang, in Proceedings of the 18th International Conference on Educational Data Mining (EDM), 2025

• Content knowledge identification with multi-agent large language models (LLMs), Kaiqi Yang, Yucheng Chu, Taylor Darwin, Ahreum Han, Hang Li, Hongzhi Wen, Yasemin Copur-Gencturk, Jiliang Tang, Hui Liu, in Proceedings of the 25th International Conference on Artificial Intelligence in Education (AIED), 2024