- Bias Association Discovery Framework for Open-Ended LLM Generation (AAAI 2026)
- What’s Not Said Still Hurts: A Description-Based Evaluation Framework for Measuring Social Bias in LLMs (EMNLP 2025 Findings)
- Combating Heterogeneous Model Biases in Recommendations via Boosting (WSDM 2025)
Research Experience
Currently a second-year Ph.D. student at George Mason University, working under the guidance of Prof. Ziwei Zhu. Previously, conducted research while pursuing a Master's degree at Texas A&M University.
Education
Ph.D. student in the Department of Computer Science at George Mason University, advised by Prof. Ziwei Zhu; Master’s degree in Computer Science from Texas A&M University, advised by Prof. James Caverlee; Bachelor’s degree in Computer Engineering from Texas A&M University, member of TAMU Corps of Cadets for four years.
Background
Broadly interested in LLMs, machine learning, data mining, and information retrieval, specifically in enhancing AI-powered systems’ responsibility, fairness, and trustworthiness to better serve both users and society. Current research focuses on discovering and mitigating biases in LLMs.
Miscellany
Actively seeking a research internship for Summer 2026.