Zilong Zhang

Zilong Zhang

I am a Ph.D. student in Machine Learning & Data Science in the Math & Statistics Department at Georgia State University, advised by Dr. Chi-Kuang Yeh. I previously earned an M.S. in Statistics in the Statistics & Probability Department at Michigan State University and a B.S. in Financial Mathematics through the School of Statistics at the University of International Business and Economics.

Research Interests

My research develops statistical methods for reliable, uncertainty-aware inference, with functional data analysis at its core and a growing focus on the trustworthy evaluation of large language models.

• Functional Data Analysis (FDA): functional time series, long-run covariance estimation, bandwidth selection, and functional principal component analysis
• Trustworthy LLM Evaluation: auditing LLM-as-a-judge systems, positive–unlabeled learning for evaluation, and uncertainty quantification for AI evaluators
• Statistical Machine Learning: uncertainty quantification, statistical theory of deep learning, and graph neural networks with applications to biological and single-cell data

News

• Oct 2026: Received a NeurIPS 2026 Financial Assistance Award, covering full conference and workshop registration in Atlanta.
• Oct 2026: Presented the poster Quantifying and Auditing LLM Evaluation via Positive–Unlabeled Learning at Georgia Statistics Day 2026, Georgia Tech, Atlanta.

Selected Publications

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