Shengyi He

About Me

I'm currently a fifth-year PhD student at Columbia IEOR advised by Prof. Henry Lam. Before joing Columbia IEOR, I obtained my B.S. degree in Statistics from the School of Mathematical Science at Peking University. My research topics include error reduction and uncertainty quantification in Monte Carlo methods and stochastic optimization.

Publications

Journal Papers

• Adaptive importance sampling for efficient stochastic root finding and quantile estimation, with Michael Fu, Guangxin Jiang, and Henry Lam, Articles in Advance, Operations Research, 2023.

• Higher-order coverage errors of batching methods via Edgeworth expansions on t-statistics, with Henry Lam, to appear in Annals of Statistics.

• Certifiable deep importance sampling for rare-event simulation of black-box systems, with Mansur Arief, Yuanlu Bai, Wenhao Ding, Zhiyuan Huang, Henry Lam, and Ding Zhao, under minor revision in Operations Research.

• Higher-order expansion and Bartlett correctability of distributionally robust optimization, with Henry Lam, under revision in Mathematics of Operations Research.

• Robust sensitivity analysis to assess input distributional uncertainty: Asymptotic approximations and computations, with Henry Lam, in preparation.

• Achieving higher-order coverage accuracy with computationally cheaper iterated bootstraps, with Henry Lam, in preparation.

• Statistical optimality in low-computation uncertainty quantification, with Henry Lam, in preparation.

Conference Proceedings

• Deep Probabilistic Accelerated Evaluation: A robust certifiable rare-event simulation methodology for black-box safety-critical systems, with Mansur Arief, Zhiyuan Huang, Guru Koushik Senthil Kumer, Yuanlu Bai, Wenhao Ding, Henry Lam, and Ding Zhao, Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.

• Higher-order coverage error analysis for batching and sectioning, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC) , 2021.
  WSC 2021 INFORMS I-SIM PhD Colloquium Award

• Batching on biased estimators, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC), 2022.

• Importance sampling for rare-event gradient estimation, with Yuanlu Bai, Henry Lam, Guangxin Jiang, and Michael Fu, Proceedings of the Winter Simulation Conference (WSC), 2022.

• Optimal batching under computation budget, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC), 2023.