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HU Zhaolin
HU Zhaolin


Department: Management Science and Engineering



  • 20082011: Ph.D. in Industrial Engineering and Logistics Management, The Hong Kong University of Science and Technology
  • 20042008: B.Sc. in Mathematics and Applied Mathematics, Zhejiang University

Teaching Experience

  • Undergraduate (Tongji University):  1. Decision Simulation; 2. Management Modeling and Simulation (Fall 2012); 3. Operations Research (Spring 2013)
  • Postgraduate (Tongji University):  1. Advanced Applied Statistics; 2. Stochastic Programming; 3. Operations Research (Fall 2012)
  • Teaching Assistant at HKUST: EEMT 512 Operations Management; IELM 313 System Simulation; IELM 320 Facilities Layout and Material Handling; IELM 341 Global Supply Chain Management; IELM 311 Engineers in Society


  • 2018-Now: Professor; 2014-2017: Associate Professor; 2012-2013: Assistant Professor; 2011-2012: Faculty, School of Economics and Management, Tongji University

International Experience

  • 2014/08, 2012/07-08, Research Fellow, Department of Management Science, College of Business, City University of Hong Kong;
  • 2013/07-08, Research Fellow, Department of Industrial Engineering and Logistics Management, HKUST;
  • 2008-2011, HKUST, Ph.D student;
  • Delivering presentations on various international conferences, e.g., INFORMS Annual Meeting, Winter Simulation Conference, INFORMS International Conference, POMS-HK International Conference

Research Interests

  • Stochastic Optimization
  • Simulation Theory and Practice
  • Machine Learning
  • Financial Risk Management
  • Intelligent Decision

Sponsored Research Projects

  • “High Dimensional Simulation Optimization and Its Applications in Inventory Logistics System Operations” (PI), Natural Science Foundation of China Grant, Project No. 72071148, 2021.01-2024.12.
  • “Stochastic Optimization, Decision under Uncertainty” (PI), Natural Science Foundation of China Grant, National Science Fund for Excellent Young Scholars, Project No. 71722009, 2018.01-2020.12.
  • Tongji University 100 Youth Program A, 2018-2022.
  • Tongji University 100 Youth Program B, 2017.
  • “Input uncertainty in simulation with applications in financial risk management” (PI), Natural Science Foundation of China Grant, Project No. 71201117, 2013.01-2015.12.
  • “Management and decision based on distributionally robust optimization” (PI), Shanghai Pujiang Program. Project No. 13PJC101. 2013.09-2015.08.
  • “Life cycle oriented quality & safety management and resource deployment optimization for health care services”, Participant, Natural Science Foundation of China Grant, Key Project, 2015-2019.

Journal Papers

  • [J]. Hu, Z., W. Sun, S. Zhu. Chance constrained programs with Gaussian mixture models. IISE Transactions, Accepted.
  • [J]. Zheng, X., Y. Pan, Z. Hu*. 2021. Perspective reformulations of semi-continuous quadratically constrained quadratic programs. INFORMS Journal on Computing, 33(1) 163-179. *Corresponding author
  • [J]. Hu, Z., D. Zhang. 2018. Utility-based shortfall risk: efficient computations via Monte Carlo. Naval Research Logistics, 65 378–392.
  • [J]. Sun, L., L. J. Hong, Z. Hu. 2014. Balancing exploitation and exploration in discrete optimization via simulation through a Gaussian process-based search. Operations Research, 62(6) 1416-1438.
  • [J]. Hong, L. J., Z. Hu., G. Liu. 2014. Monte Carlo methods for value-at-risk and conditional value-at-risk: A review. ACM Transactions on Modeling and Computer Simulation, 24(4) Article 22.
  • [J]. Hong, L. J., Z. Hu*, L. Zhang. 2014. Conditional value-at-risk approximation to value-at-risk constrained programs: A remedy via Monte Carlo. INFORMS Journal on Computing, 26(2) 385-400. *Corresponding author
  • [J]. Hu, Z., L. J. Hong, L. Zhang. 2013. A smooth Monte Carlo approach to joint chance constrained programs. IIE Transactions, 45(7) 716-735.
  • [J]. Hu, Z., J. Cao, L. J. Hong. 2012. Robust simulation of global warming policies using the DICE model. Management Science, 58(12) 2190-2206.

Working Papers 

  • [W]. Hu, Z., L. J. Hong. Robust simulation with likelihood-ratio constrained input

    • An earlier version: Robust simulation of stochastic systems. [PDF].
  • [W]. Hu, Z., L. J. Hong, A. M. C. So. 2013. Ambiguous probabilistic programs. [Optimization Online].
  • [W]. Hu, Z., L. J. Hong. 2012. Kullback-Leibler divergence constrained distributionally robust optimization. [Optimization Online]. Google Scholar Citations over 100.

Conference Papers

  • [C]. Sun, W., Z. Hu, L. J. Hong. 2018. Gaussian mixture model-based random search for continuous optimization via simulation. Proceedings of the 2018 Winter Simulation Conference, 2003-2014.
  • [C]. Hu, Z., L. J. Hong. 2015.  Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences. Proceedings of the 2015 Winter Simulation Conference, 643-654.
  • [C]. Sun, L., L. J. Hong, Z. Hu. 2011. Optimization via simulation using Gaussian process-based search. Proceedings of the 2011 Winter Simulation Conference, 4134-4145.
  • [C]. Hu, Z., J. Cao, L. J. Hong. 2010. Robust simulation of environmental policies using the DICE model. Proceedings of the 2010 Winter Simulation Conference, 1295-1305.


  • [PC] Input modeling and its interactions with solution approaches for chance constrained programs, 2018 MS/IE Workshop on Smart Simulation, Peking University, June, 2018;
  • [PC] Balancing exploitation and exploration in continuous simulation optimization, INFORMS International Conference, June, 2018;
  • [PC] Chance constrained programs with mixture distributions, University of Shanghai for Science and Technology, September, 2017;
  • [PC] Input modeling for chance constrained programs with mixture distributions, The Second Tianfu Workshop on Financial Mathematics, Chengdu, China, July 2017;
  • [PC] Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences, Winter Simulation Conference, Los Angeles, USA, December 2015;
  • [PC] Convex Risk Measures: Efficient Computations via Monte Carlo, ICCOPT, Tokyo, Japan, August 2016; INFORMS Annual Meeting, Philadelphia, USA, November 2015;
  • [PC] Convex Risk Measures: Efficient Computations via Monte Carlo, The Fifth Annual Meeting of Financial Engineering and Financial Risk Management Branch of OR Society of China, Guizhou University, Guizhou, China, July 2015;
  • [PC] Emergency medical services location: A stochastic double standard model, Workshop on Risk Management and Stochastic Optimization, Nanjing University of Science and Technology, June 2016; Lingnan (University) College, Sun Yat-sen University, Guangzhou, China, October 2015; 2015 Asian Conference of Management Science & Applications, Dongbei University of Finance and Economics, Dalian, China, September 2015;
  • [PC] Optimization of Probability and Convex Risk Measures: A Monte Carlo Approach, Shanghai Finance University, Shanghai, China, April 2015;
  • [PC] Optimization and Uncertainty Issue of Probability and Value-at-risk, Workshop on Advanced Optimization Theory and Applications in Finance, Shanghai University of Finance and Economics, Shanghai, China, October 2014;
  • [PC] Robust Simulation of Stochastic Systems with Input Uncertainty Modeled by Statistical Divergences, 2014 OM/MS Mini-workshop On Operations Management and Analytics, Shanghai Jiao Tong University, Shanghai, China, October 2014;
  • [PC] Ambiguous probabilistic programs, INFORMS Annual Meeting, Minneapolis, Minnesota, USA, October 2013; East Asian Simulation Workshop, HKUST, Hong Kong, China, August 07, 2013; Hong Kong Optimization Day, The Hong Kong Polytechnic University, Hong Kong, China, July 18, 2013;
  • [PC] Kullback-Leibler divergence constrained distributionally robust optimization, The Fourth POMS-HK International Conference, City University of Hong Kong, Hong Kong, China, January 2013;
  • [PC] CVaR approximation to VaR constrained programs: A remedy, INFORMS Beijing International Conference, Beijing, China, June 2012;
  • [PC] CVaR approximation to chance constrained program: What is lost and how to recover it? The Second POMS-HK International Conference, Hong Kong, China, January 2011;
  • [PC] A kriging based tradeoff between exploration and exploitation, INFORMS Annual Meeting, Austin, TX, USA, November 2010;
  • [PC] Robust simulation of environmental policies, INFORMS Annual Meeting, Austin, TX, USA, November 2010;
  • [PC] Robust simulation of environmental policies using the DICE model, The Third International Annual Conference of The Overseas Chinese Scholars Association in Management Science and Engineering (OCSAMSE), , Beijing, China, July 2010;

Research Group

  • PHD students:

WEI Jinxiang

GUO Jian

ZHANG Wenchu

  • Master students:

GAO Yuhan: Graduated, 2021

LI Jing: Graduated, 2020

SUN Wenjie: Graduated, 2019

MA Xiaoyi (co-supervised): Graduated, 2019

LIU Caifeng: Graduated, 2019

  • Visiting students:

CHEN Zhixi: Summer, 2019. Master student from University of Michigan, Ann Arbor

Some Useful Links

Referee Service

  • Journal of Management Science and Engineering, Associate Editor (2016-)
  • Reviewer for Operations Research, Production and Operations Management, IEEE Transactions on Automatic Control, Naval Research Logistics, European Journal of Operational Research, Asia-Pacific Journal of Operational Research, Journal of Industrial and Management Optimization, Winter Simulation Conference, IEEE Conference on Decision and Control
  • Track committee member for 2013 Winter Simulation Conference
  • Technical program committee member for 2016-2020 Winter Simulation Conference
  • Youth Job Expert, Tongji University, 2012
  • Institute of Industrial Engineers (IIE) Pritsker Doctoral Dissertation Award, 3rd place, 2012
  • Postgraduate Studentship at HKUST
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