个人简介
教育背景
博士,工业工程及管理科学,美国西北大学
硕士,应用数学,美国辛辛那提大学
学士,汽车工程,清华大学
科研项目
2022.01 - 2025.12, 项目负责人, 基于蒙特卡洛仿真的系统性金融风险管理的理论与方法, 国家自然科学基金国际（地区）合作与交流项目
2021.01 - 2025.12, 课题负责人, 基于智能仿真的平台供应链风险管理, 国家自然科学基金重大项
学术任职
2018.01 - 至今, Simulation Area Editor, Operations Research
2018.01 - 至今, Associate Editor, Management Science
2018.01 - 2022.12, Vice-President/President-Elect, INFORMS Simulation Society
2017.01 - 2020.12, 第十届理事会理事, 中国运筹学会
2008.01 - 2017.12, Area Editor, Operations Research
2007.01 - 至今, Associate Editor, ACM Transactions on Modeling and Computer Simulation
近期论文
查看导师最新文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
Xiuxian Wang, L. Jeff Hong, Zhibin Jiang, and Haihui Shen. 2023. Gaussian process-based random search for continuous optimization via simulation. Operations Research forthcoming.1-23.
L. Jeff Hong, Guangwu Liu, Jun Luo, and Jingui Xie. 2023. Variability scaling and capacity planning in Covid-19 pandemic. Fundamental Research 3(4).627-639.
Wenhao Li, Zhankun Sun, and L. Jeff Hong. 2023. Who is next: Patient prioritization under emergency department blocking. Operations Research 71(3).821-842.
Tan Wang and L. Jeff Hong. 2023. Large-scale inventory optimization: A recurrent neural networks–inspired simulation approach. INFORMS Journal on Computing 35(1).196-215.
Wenhao Li, Ningyuan Chen, and L. Jeff Hong. 2023. Dimension reduction in contextual online learning via nonparametric variable selection. Journal of Machine Learning Research 24(136).1-84.
L. Jeff Hong, Guangxin Jiang, and Ying Zhong. 2022. Solving large-scale fixed-budget ranking and selection problems. INFORMS Journal on Computing 34(6).2930-2949.
Zhaolin Hu and L. Jeff Hong. 2022. Robust simulation with likelihood-ratio constrained input uncertainty. INFORMS Journal on Computing 34(4).2350-2367.
Yifan Zhang, Jinghuai Zhang, Jindi Zhang, and Jianping Wang, Kejie Lu, and Jeff Hong. 2022. Integrating algorithmic sampling-based motion planning with learning in autonomous driving. ACM Transactions on Intelligent Systems and Technology 13(3).1-27.
Liang Ding, L. Jeff Hong, Haihui Shen, and Xiaowei Zhang. 2022. Technical note—Knowledge gradient for selection with covariates: Consistency and computation. Naval Research Logistics 69(3).496-507.
Xi Jiang , Barry L. Nelson, and L. Jeff Hong. 2022. Meaningful sensitivities: A new family of simulation sensitivity measures. IISE Transactions 54(2).122-133.
Ying Zhong, Shaoxuan Liu, Jun Luo, and L. Jeff Hong. 2022. Speeding up paulson's procedure for large-scale problems using parallel computing. INFORMS Journal on Computing 34(1).586-606.
Ying Zhong and L. Jeff Hong. 2022. Knockout-Tournament procedures for large-scale ranking and selection in parallel computing environments. Operations Research 70(1).432-453.
Yijie Peng, Li Xiao, Bernd Heidergott, L. Jeff Hong, and Henry Lam. 2022. A new likelihood ratio method for training artificial neural networks. INFORMS Journal on Computing 34(1).638-655.
L. Jeff Hong, Weiwei Fan, and Jun Luo. 2021. Review on ranking and selection: A new perspective. Frontier of Engineering Management 8(3).321–343.
Haihui Shen, L. Jeff Hong, and Xiaowei Zhang. 2021. Ranking and selection with covariates for personalized decision making. INFORMS Journal on Computing 33(4).1500-1519.
Ying Zhong, L. Jeff Hong, and Guangwu Liu. 2021. Earning and learning with varying cost. Production and Operations Management 30(8).2379–2394.
L. Jeff Hong, Zhiyuan Huang, and Henry Lam. 2021. Learning-based robust optimization: procedures and statistical guarantees. Management Science 67(6).3447–3467.
L. Jeff Hong, Chenghuai Li, and Jun Luo. 2020. Technical note: Finite‐time regret analysis of Kiefer‐Wolfowitz stochastic approximation algorithm and nonparametric multi‐product dynamic pricing with unknown demand. Naval Research Logistics 67(5).368-379.
Guangxin Jiang, L. Jeff Hong, and Barry L. Nelson. 2020. Online risk monitoring using offline simulation. INFORMS Journal on Computing 32(2).356-375.
Weiwei Fan, L. Jeff Hong, and Xiaowei Zhang. 2020. Distributionally robust selection of the best. Management Science 66(1).190-208.
L. Jeff Hong and Guangxin Jiang. 2019. Offline simulation online application: A new framework of simulation-based decision making. Asia-Pacific Journal of Operational Research 36(6).1-22.
Xin Yun, L. Jeff Hong, Guangxin Jiang, and Shouyang Wang. 2019. On gamma estimation via matrix kriging. Naval Research Logistics 66(5).393-410.
Haihui Shen, L. Jeff Hong, and Xiaowei Zhang. 2018. Enhancing stochastic kriging for queueing simulation with stylized models. IISE Transactions 50(11).943–958.
Fang Jin and L. Jeff Hong. 2018. A simulation-based estimation method for bias reduction. IISE Transactions 50(1).14-26.
L. Jeff Hong and Guang-Xin Jiang. 2017. Gradient and hessian of joint probability function with applications on chance-constrained programs. Journal of the Operations Research Society of China 5(4).431-455.
L. Jeff Hong, Sandeep Juneja, and Guangwu Liu. 2017. Kernel smoothing for nested estimation with application to portfolio risk measurement. Operations Research 65(3).657–673.
Weiwei Fan, L. Jeff Hong, and Barry L. Nelson. 2016. Indifference-zone-free selection of the best. Operations Research 64(6).1499-1514.
Jun Luo, L. Jeff Hong, Barry L. Nelson, and Yang Wu. 2015. Fully sequential procedures for large-scale ranking-and-selection problems in parallel computing environments. Operations Research 63(5).1177-1194.
L. Jeff Hong, Xiaowei Xu, and Sheng Hao Zhang. 2015. Capacity reservation for time-sensitive service providers: An application in seaport management. European Journal of Operational Research 245(2).470-479.
L. Jeff Hong, Jun Luo, and Barry L. Nelson. 2015. Chance constrained selection of the best. INFORMS Journal on Computing 27(2).317-334.
Lihua Sun, L. Jeff Hong, and Zhaolin Hu. 2014. Balancing exploitation and exploration in discrete optimization via simulation through a gaussian process-based search. Operations Research 62(6).1416-1438.
L. Jeff Hong, Sandeep Juneja, and Jun Luo. 2014. Estimating sensitivities of portfolio credit risk using Monte Carlo. INFORMS Journal on Computing 26(4).645-914.
L. Jeff Hong, Zhaolin Hu, and Guangwu 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).22:1-37.
L. Jeff Hong, Zhaolin Hu, and Liwei 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.
Jie Xu, Barry L. Nelson, and L. Jeff Hong. 2013. An adaptive hyperbox algorithm for high-dimensional discrete optimization via simulation problems. INFORMS Journal on Computing 25(1).133-146.
Zhaolin Hu, L. Jeff Hong, and Liwei Zhang. 2013. A smooth Monte Carlo approach to joint chance-constrained programs. IIE Transactions 45(7).716-735.
Kuo-Hao Chang, L. Jeff Hong, and Hong Wan. 2013. Stochastic trust-region response-surface method (STRONG) - A new response-surface framework for simulation optimization. INFORMS Journal on Computing 25(2).230-243.
Zhaolin Hu, Jing Cao, and L. Jeff Hong. 2012. Robust simulation of global warming policies using the DICE model. Management Science 58(12).2190-2206.
Jie Zhang, L.Jeff Hong, and Rachel Q. Zhang. 2012. Fighting strategies in a market with counterfeits. Annals of Operations Research 192(1).49-66.
L. Jeff Hong, Yi Yang, and Liwei Zhang. 2011. Sequential convex approximations to joint chance constrained programs: A Monte Carlo approach. Operations Research 59(3).617-630.
Guangwu Liu and L. Jeff Hong. 2011. Kernel estimation of the Greeks for options with discontinuous payoffs. Operations Research 59(1).96-108.
L. Jeff Hong, Barry L. Nelson, and Jie Xu. 2010. Speeding up COMPASS for high-dimensional discrete optimization via simulation. Operations Research Letters 38(6).550-555.
Lihua Sun and L. Jeff Hong. 2010. Asymptotic representations for importance-sampling estimators of value-at-risk and conditional value-at-risk. Operations Research Letters 38(4).246-251.
L. Jeff Hong and Guangwu Liu. 2010. Pathwise estimation of probability sensitivities through terminating or steady-state simulations. Operations Research 58(2).357-370.
Jie Xu, Barry L Nelson, and L. Jeff Hong. 2010. Industrial strength compass: a comprehensive algorithm and software for optimization via simulation. ACM Transactions on Modeling and Computer Simulation 20(1).3:1-29.
Michael C. Fu, L.Jeff Hong, Jianqiang Hu. 2009. Conditional Monte Carlo Estimation of Quantile Sensitivities. Management Science 55(12).2019-2027.
Guangwu Liu and L. Jeff Hong. 2009. Revisit of stochastic mesh method for pricing American options. Operations Research Letters 37(6).411-414.
Guangwu Liu and Liu Jeff Hong. 2009. Kernel estimation of quantile sensitivities. Naval Research Logistics 56(6).511-525.
L. Jeff Hong and Guangwu Liu. 2009. Simulating sensitivities of conditional value at risk. Management Science 55(2).281-293.
L. Jeff Hong. 2009. Estimating quantile sensitivities. Operations Research 57(1).118-130.
L. Jeff Hong and Barry L. Nelson. 2007. A framework for locally convergent random-search algorithms for discrete optimization via simulation. ACM Transactions on Modeling and Computer Simulation 17(4).1-22.
L. Jeff Hong and Barry L. Nelson. 2007. Selecting the best system when systems are revealed sequentially. IIE Transactions 39(7).723-734.
Juta Pichitlamken, Barry L. Nelson, and L. Jeff Hong. 2006. A sequential procedure for neighborhood selection-of-the-best in optimization via simulation. European Journal of Operational Research 173(1).283-298.
L. Jeff Hong. 2006. Fully sequential indifference-zone selection procedures with variance-dependent sampling. Naval Research Logistics 53(5).464-476.
L. Jeff Hong and Barry L. Nelson. 2006. Discrete optimization via simulation using COMPASS. Operations Research 54(1).115-129.
L. Jeff Hong and Barry L. Nelson. 2005. The tradeoff between sampling and switching: New sequential procedures for indifference-zone selection. IIE Transactions 37(7).623-634.
会议/研讨会论文
Ying Zhong and L. Jeff Hong. 2017. A new framework of designing sequential ranking-and-selection procedures. Proceedings of the 2017 Winter Simulation Conference Las Vegas, USA.2237-2244.
Haihui Shen, L. Jeff Hong, and Xiaowei Zhang. 2017. Ranking and selection with covariates. Proceedings of the 2017 Winter Simulation Conference Las Vegas, USA.2137-2148.
L. Jeff Hong, Zhiyuan Huang, and Henry Lam. 2016. Approximating data-driven joint chance-constrained programs via uncertainty set construction. Proceedings of the 2016 Winter Simulation Conference Arlington, USA.389-400.
L. Jeff Hong, Jun Luo, and Ying Zhong. 2016. Speeding up pairwise comparisons for large scale ranking and selection. Proceedings of the 2016 Winter Simulation Conference Arlington, USA.749-757.
Guangxin Jiang, L. Jeff Hong, and Barry L. Nelson. 2016. A simulation analytics approach to dynamic risk monitoring. Proceedings of the 2016 Winter Simulation Conference Arlington, USA.437-447.
Zhaolin Hu and L. Jeff Hong. 2015. Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences. Proceedings of the 2015 Winter Simulation Conference Huntington Beach, USA.643-654.
L. Jeff Hong and Henry Lam. 2015. A statistical perspective on linear programs with uncertain parameters. Proceedings of the 2015 Winter Simulation Conference Huntington Beach, USA.3690-3701.
Eunhye Song, Barry L. Nelson, and L. Jeff Hong. 2015. Input uncertainty and indifference-zone ranking and selection. Proceedings of the 2015 Winter Simulation Conference Huntington Beach, USA.414-424.
Weiwei Fan and L. Jeff Hong. 2015. A frequentist selection-of-the-best procedure without indifference zone. Proceedings of the 2014 Winter Simulation Conference Savannah, USA.3737-3748.
Xiaowei Zhang, L. Jeff Hong, and Jiheng Zhang. 2014. Scaling and modeling of call center arrivals. Proceedings of the 2014 Winter Simulation Conference Savannah, USA.476-485.
Jin Fang and L. Jeff Hong. 2013. Linking statistical estimation and decision making through simulation. Proceedings of the 2013 Winter Simulation Conference Washington, USA.766-777.
Weiwei Fan, L. Jeff Hong, and Xiaowei Zhang. 2013. Robust selection of the best. Proceedings of the 2013 Winter Simulation Conference Washington, USA.868-876.
Jun Luo and L. Jeff Hong. 2011. Large-scale ranking and selection using cloud computing. Proceedings of the 2011 Winter Simulation Conference Phoenix, USA.4051-4061.
L. Jeff Hong and Guangwu Liu. 2011. Monte Carlo estimation of value-at-risk, conditional value-at-risk and their sensitivities. Proceedings of the 2011 Winter Simulation Conference Phoenix, USA.95-107.
Lihua Sun, L. Jeff Hong, and Zhaolin Hu. 2011. Optimization via simulation using Gaussian process-based search. Proceedings of the 2011 Winter Simulation Conference Phoenix, USA.4139-4150.
Zhaolin Hu, Jing Cao, and L. Jeff Hong. 2010. Robust simulation of environmental policies using the dice model. Proceedings of the 2010 Winter Simulation Conference Baltimore, USA.1295-1305.
L. Jeff Hong and Barry L. Nelson. 2009. A brief introduction to optimization via simulation. Proceedings of the 2009 Winter Simulation Conference Austin, USA.75-85.
L. Jeff Hong and Sandeep Juneja. 2009. Estimating the mean of a non-linear function of conditional expectation. Proceedings of the 2009 Winter Simulation Conference Austin, USA.1223-1236.
Lihua Sun and L. Jeff Hong. 2009. A general framework of importance sampling for value-at-risk and conditional value-at-risk. Proceedings of the 2009 Winter Simulation Conference Austin, USA.415-422.
Guangwu Liu and L. Jeff Hong. 2008. Revisit of stochastic mesh method for pricing American options. Proceedings of the 2008 Winter Simulation Conference Miami, USA.594-601.
Nan Chen and L. Jeff Hong. 2007. Monte-Carlo simulation in financial engineering. Proceedings of the 2007 Winter Simulation Conference Washington, USA.919-931.
Kuo-Hao Chang, L. Jeff Hong, and Hong Wan. 2007. Stochastic trust region gradient-free method (strong) - a new response-surface-based algorithm in simulation optimization. Proceedings of the 2007 Winter Simulation Conference Washington, USA.346-354.
L. Jeff Hong. 2005. Discrete optimization via simulation using coordinate search. Proceedings of the 2005 Winter Simulation Conference Orlando, USA.803-810.
L. Jeff Hong and Barry L. Nelson. 2003. An indifference-zone selection procedure with minimum switching and sequential sampling. Proceedings of the 2003 Winter Simulation Conference New Orleans, USA.474-480.
著作中的文章
L. Jeff Hong and Xiaowei Zhang. Surrogate-based simulation optimization.In INFORMS TutORials in Operations Research. Institute for Operations Research and the Manageme, 2021.
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