Chengpiao Huang

I am a third-year PhD student in the Department of Industrial Engineering and Operations Research at Columbia University, advised by Professor Kaizheng Wang.

Prior to joining Columbia, I received my Bachelor's degree in Mathematics and Applied Mathematics at The Chinese University of Hong Kong, Shenzhen.

E-mail: chengpiao.huang [AT] columbia [DOT] edu
CV Google Scholar

Research Interests

I am interested in statistical machine learning and online learning. Recently I have been working on learning under distribution shift.

I am honored to receive the Outstanding Teaching Assistant Award in Columbia IEOR.
Our paper “Uncertainty Quantification for LLM-Based Survey Simulations” is accepted at ICML 2025.
Our paper “A Stability Principle for Learning under Non-Stationarity” is accepted by Operations Research.
Our paper “Distribution-Free Predictive Inference under Unknown Temporal Drift” is posted on arXiv.
Our paper “Model Assessment and Selection under Temporal Distribution Shift” is accepted at ICML 2024.
We (Kaizheng Wang, Yuhang Wu and I) won second place in the 2023 INFORMS Blue Summit Supplies Data Challenge! We also ranked first in the two-week live test of pricing and profit forecasting.