Huajie Qian
Contact Information
205 108th Ave. NE, Suite 400
Bellevue, WA 98004

Email: h.qian@columbia.edu
Website: http://www.columbia.edu/~hq2157/

Employment
Alibaba Group (US) Inc., Bellevue, WA

July 2020-present

Research Interests
Statistical uncertainty quantification, data-driven simulation, stochastic and robust optimization

Education
Columbia University, New York, NYJan 2018-May 2020

Ph.D. in Operations Research
Advisor: Henry Lam
University of Michigan, Ann Arbor, MI

Sept 2014-Dec 2017

M.S. in Applied and Interdisciplinary Mathematics
Overall GPA: 4.00/4.00
Fudan University, Shanghai, China

Sept 2010-July 2014

B.S. in Mathematics, Outstanding Graduate of Shanghai (top 5%)
Major GPA: 3.87/4.00, Class Rank 1/53

Publications
Journal Articles• H. Lam and H. Qian, Subsampling to enhance efficiency in input uncertainty quantification, Operations
Research, 70(3):1891-1913, 2022.
• A. Goeva, H. Lam, H. Qian and B. Zhang, Optimization-based calibration of simulation input models,Operations Research, 67(5):1362-1382, 2019.
• H. Lam and H. Qian, Optimization-based quantification of simulation input uncertainty via empirical likelihood, under revision in Management Science, URL: https://arxiv.org/abs/1707.05917.
• H. Lam and H. Qian, Combating conservativeness in data-driven optimization under uncertainty: A solution
path approach, under revision in Management Science, URL: https://arxiv.org/abs/1909.06477.
• H. Lam and H. Qian, Bounding optimality gap in stochastic optimization via bagging: Statistical efficiencyand stability, under revision in Operations Research, URL: https://arxiv.org/abs/1810.02905.
• X. Wang, H. Qian and S. Zhang, Discovery of significant pathways in breast cancer metastasis via module
extraction and comparison, IET Systems Biology 8(2):47-55, 2014.
Refereed Conference Proceedings• Z. Chen, J. Lu, H. Qian, X. Wang and W. Yin, HeteRSGD: Tackling heterogeneous sampling costs viaCurriculum Vitae, Huajie Qian, 1optimal reweighted stochastic gradient descent, Proceedings of the 26th International Conference on Artificial
Intelligence and Statistics (AISTATS), 2023.
• Z. Zhou, C. Zhang, L. Ma, J. Gu, H. Qian, Q. Wen, L. Sun, P. Li and Z. Tang, AHPA: Adaptive horizontal
pod autoscaling systems on Alibaba Cloud Container Service for Kubernetes, AAAI/IAAI/EAAI, 2023.
• H. Qian, Q. Wen, L. Sun, J. Gu, Q. Niu and Z. Tang, RobustScaler: QoS-aware autoscaling for complex
workloads, Proceedings of the 38th International Conference on Data Engineering (ICDE), 2022.
• Y. Zhang, Z. Guan, H. Qian, L. Xu, H. Liu, Q. Wen, L. Sun, J. Jiang, L. Fan and M. Ke, CloudRCA: Aroot cause analysis framework for cloud computing platforms, Proceedings of the 30th ACM International
Conference on Information and Knowledge Management (CIKM), 2021.
• H. Chen, Z. Huang, H. Lam, H. Qian and H. Zhang, Learning prediction intervals for regression: Generalization and calibration, Proceedings of the 24th International Conference on Artificial Intelligence and Statistics(AISTATS), 2021.
• H. Lam and H. Qian, Validating optimization with uncertain constraints, Proceedings of the 2019 WinterSimulation Conference (WSC).
• H. Lam and H. Qian, Random perturbation and bagging to quantify input uncertainty, Proceedings of the2019 Winter Simulation Conference (WSC).
• H. Lam and H. Qian, Assessing solution quality in stochastic optimization via bootstrap aggregating, Proceedings of the 2018 Winter Simulation Conference (WSC), 2061-2071.
• H. Lam and H. Qian, Subsampling variance for input uncertainty quantification, Proceedings of the 2018
Winter Simulation Conference (WSC), 1611-1622.
• H. Lam and H. Qian, The empirical likelihood approach to simulation input uncertainty, Proceedings of the2016 Winter Simulation Conference (WSC), 791-802.

Honors & Awards
AAAI/IAAI Deployed Application Award

2023

Winter Simulation Conference Travel Scholarship, WSC Foundation2018

Rackham Conference Travel Grant, University of Michigan

2016-2017

thFunding from the organizers of the 26 IAS(Institute for Advanced Study)/PCMI(Park City Mathematics Institute) Graduate Summer School
Mathematics Department Graduate Fellowship, University of Michigan

2016
2015-2017

Chia-Chiao Lin Bronze Medal (ranked 5th nationwide), the 4th Shing-Tung Yau College Math Contests
Team Bronze Medal (ranked 6thFirst-Class (ranked 18ththnationwide), the 4thnationwide), the 4

Shing-Tung Yau College Math Contests

China College Math Contests

2013
2013
2013

China National Scholarship (top 2%), Ministry of Education of China

2013

Talks
HeteRSGD: Tackling Heterogeneous Sampling Costs via Optimal Reweighted Stochastic Gradient Descent• International Conference on Artificial Intelligence and Statistics (AISTATS), Valencia, Spain, April 2023
Robust QoS-Aware Autoscaling for Complex Workloads in Cloud Computing• International Conference on Data Engineering (ICDE), Kuala Lumpur, Malaysia, May 2022
Random Perturbation to Quantify Input UncertaintyCurriculum Vitae, Huajie Qian, 2• Winter Simulation Conference (WSC), National Harbor, MD, Dec 2019
Combating Conservativeness in Optimization under Uncertain Constraints• Workshop on Optimization, Probability, and Optimization (WOPS), Shenzhen, China, Dec 2020
• INFORMS Annual Meeting, virtual, Nov 2020
• Winter Simulation Conference (WSC), National Harbor, MD, Dec 2019
• INFORMS Annual Meeting, Seattle, WA, Oct 2019
• Cornell Young Researchers Workshop, Ithaca, NY, Oct 2019
• International Conference on Continuous Optimization, Berlin, Germany, Aug 2019
• Mostly OM Workshop, Shenzhen, China, June 2019
• International Symposium on Mathematical Programming (ISMP), Bordeaux, France, July 2018
Subsampling Estimation of Simulation Input Uncertainty• INFORMS Applied Probability Society Conference (APS), Brisbane, Australia, July 2019
• Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec 2018
• INFORMS Annual Meeting, Houston, TX, Oct 2017
Assessing Solution Quality in Stochastic Optimization via Bootstrap Aggregating• INFORMS Applied Probability Society Conference (APS), Brisbane, Australia, July 2019
• Winter Simulation Conference (WSC), Gothenburg, Sweden, Dec 2018
• PhD Student Presentation, Columbia University, Oct 2018
• Joint Statistical Meeting, Vancouver, Canada, Aug 2018
The Empirical Likelihood Approach to Simulation Input Uncertainty• INFORMS Annual Meeting, Houston, TX, Oct 2017
• INFORMS Applied Probability Society Conference (APS), Evanston, IL, July 2017
• Winter Simulation Conference (WSC), Washington, D.C., Dec 2016
• INFORMS Annual Meeting, Nashville, TN, Nov 2016
Optimization-Based Calibration of Simulation Input Models• Joint Statistical Meeting, Vancouver, Canada, Aug 2018
Discovery of Significant Pathways in Breast Cancer Metastasis via Module Extraction and Comparison• The 12th Asian Pacific Bioinformatics Conference, Shanghai, China, Jan 2014

Teaching Experience
At University of Michigan
Lecturer, Calculus I, Winter 2015, and Pre-Calculus, Fall 2014
• Deliver four and a half hours of lectures per week to 25-30 students• Collaborate with other instructors in developing grading rubrics for two midterms and one final• Design and grade weekly quizzes

Curriculum Vitae, Huajie Qian, 3

Lab Instructor, Introduction to Differential Equations, Fall 2015, Spring 2016
• Hold four hours of recitation/computer lab meetings per week
• Instruct 100 students to solve differential equations using Matlab and Maple
Tutor in Math Lab, Department of Mathematics, Fall 2014, Winter 2015, Fall 2015
• Answer math questions from undergraduates of all levels for one hour per week

Professional Services
Student Co-organizer, Columbia IEOR-DRO Seminar
Treasurer, SIAM Student Chapter at University of Michigan
thCo-organizer, The 5

University of Michigan SIAM Student Conference

Spring 2019
Jan 2015-Dec 2017April 2015

Referee for: KDD, CIKM, PAKDD, AISTATS, SIAM Journal on Control and Optimization, SIAM/ASA Journal on Uncertainty Quantification, European Journal of Operational Research

Computer Skills
Python, C++, Matlab, R, LATEXCurriculum Vitae, Huajie Qian, 4