Huajie Qian

About Me

I'm a Ph.D. candidate in Operations Research at Columbia University. I'm currently on the academic job market for Fall 2019. My advisor is Prof. Henry Lam. Before coming to Columbia, I obtained my B.S. degree in Mathematics from Fudan University and M.S. degree in Applied and Interdisciplinary Mathematics from University of Michigan.

My research focuses on developing statistically and computationally efficient data-driven methodologies for Monte Carlo simulation and stochastic optimization.

I will present several of my works at Winter Simulation Conference 2019:

• Random Perturbation to Quantify Input Uncertainty, PhD colloquium, 4:00-5:30pm December 8th, Annapolis 4

• Random Perturbation and Bagging to Quantify Input Uncertainty, regular session, 3:30-5:00pm December 9th, Annapolis 2

• Validating Optimization with Uncertain Constraints, regular session, 8:00-9:30am December 11th, Annapolis 1

Publications

Journal Articles

• Optimization-Based Calibration of Simulation Input Models, with Aleksandrina Goeva, Henry Lam and Bo Zhang, Operations Research, 67(5):1362-1382, 2019.

• Optimization-Based Quantification of Simulation Input Uncertainty via Empirical Likelihood, with Henry Lam, under major revision in Management Science.

• Subsampling to Enhance Efficiency in Input Uncertainty Quantification, with Henry Lam, under major revision in Operations Research.

• Quantifying Simulation Input Uncertainty via Random Perturbations of Input Models, with Henry Lam, working paper.

• Combating Conservativeness in Data-Driven Optimization under Uncertainty: A Solution Path Approach, with Henry Lam, under review in Management Science.

• Bounding Optimality Gap in Stochastic Optimization via Bagging: Statistical Efficiency and Stability, with Henry Lam, in submission to Operations Research.

Refereed Conference Proceedings

• Validating Optimization with Uncertain Constraints, with Henry Lam, to appear in Proceedings of the Winter Simulation Conference (WSC), 2019.

• Random Perturbation and Bagging to Quantify Input Uncertainty, with Henry Lam, to appear in Proceedings of the Winter Simulation Conference (WSC), 2019.

• Subsampling Variance for Input Uncertainty Quantification, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC), 2018.

• Assessing Solution Quality in Stochastic Optimization via Bootstrap Aggregating, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC), 2018.

• The Empirical Likelihood Approach to Simulation Input Uncertainty, with Henry Lam, Proceedings of the Winter Simulation Conference (WSC), 2016.

Upcoming Events

• Winter Simulation Conference, National Harbor, MD, December 2019.