彭一傑，男，現任北京大學光華管理學院副教授、博士生導師，兼任北京大學人工智慧研究院兼職研究員、國家健康醫療大數據研究院特聘研究員。從事複雜系統隨機仿真最佳化的方法論與理論研究，並將新方法套用於人工智慧、金融工程與風險管理、健康醫療等領域。在Operations Research, INFORMS Journal on Computing, IEEE Transactions on Automatic Control 等期刊上發表高水平學術論文，曾獲INFORMS Outstanding Simulation Publication Award。主持國家自然科學基金優青、原創探索、傑青項目等。
基本介紹
- 中文名：彭一傑
- 國籍：中國
- 主要成就：2019年首次代表中國大陸學者獲得國際仿真領域頂尖獎項INFORMS Outstanding SimulationPublication Award
- 工作院校：北京大學
教育背景,工作經歷,教授課程,榮譽與獎勵,科研項目,期刊論文（英文）,會議論文（英文）,中文發表,學術活動,專利,
教育背景
2010.09-2014.07 復旦大學，管理學院博士，運籌學
2008.09-2010.07 復旦大學，數學科學學院研究生
2003.09-2007.07 武漢大學，數學與統計學院學士
工作經歷
2022.02- 副教授，光華管理學院，北京大學
2020.04-2022.02 助理教授，光華管理學院，北京大學
2021.1- 兼職研究員，人工智慧研究院，北京大學
2020.11- 特聘研究員，北京大學國家健康醫療大數據研究院
2017.08- 助理教授（特聘研究員），工業工程與管理系，北京大學
2016.03- 2017.08 （研究）助理教授，系統工程與運籌系，喬治梅森大學
2015.09-2016.03 博士後研究員，商學院，馬里蘭大學
2014.07-2015.08 博士後研究員，管理學院，復旦大學
2012.08-2013.08 訪問學者， 商學院，馬里蘭大學
教授課程
本科生課程：人工智慧與商業創新、仿真模型與智慧決策
研究生課程：人工智慧方法及套用
MBA/EMBA 課程：人工智慧的商務套用及其前景
榮譽與獎勵
2025 INFORMS Journal on Computing Meritorious Paper Award（優秀論文獎）
2024 教育部第九屆高等學校科學研究優秀成果二等獎
2024 北京運籌學會優秀青年論文（通訊作者\導師）
2023 北京運籌學會優秀學生論文（通訊作者\導師）
2022 北京運籌學會優秀青年論文（通訊作者\導師）
2022 冬季仿真大會仿真最佳化案例大賽第二名
2021 智慧型製造系統工程學術會議優秀論文獎
2020 冬季仿真大會最佳理論論文候選獎
2019 INFORMS 仿真社區傑出出版獎 2017 復旦大學優秀博士後
2017 IEEE 自動化大會最佳論文候選獎
2016 長三角運籌學與控制論論壇優秀論文一等獎
2014 復旦大學優秀博士論文
2013 國家獎學金
科研項目
2024.01-2028.12 智慧型管理系統仿真與最佳化，傑出青年科學基金，國家自然科學基金（主持）
2023.01-2025.12 智慧型系統的新學習方法，原創探索項目，國家自然科學基金（主持）
2021.01-2023.12 管理中的仿真最佳化，優秀青年科學基金，國家自然科學基金（主持）
2021.01-2023.12 博弈對抗條件下複雜影響因素探索性訓練學習技術，（主持）
2020.01-2022.12 數據驅動的醫療服務系統資源分配方法研究，青年科學基金， 國家自然科學基金 （主持）
2025.01-2027.12 湖南省“湘智興湘”人才項目，湖南省科技廳
2024.01-2025.12 基於強化學習的算力網路智慧運營理論與方法 ，湘江實驗室重點項目（主持）
2020.01-2020.12 數據驅動的仿真最佳化，北京市青年骨幹個人項目，北京市委組織部（主持）
2019.01-2019.12 新一代信息技術平台下的高效仿真最佳化，國際交流與合作專項，北京市科委（主持）
2016.01-2017.06 統計排序與選擇問題的理論與套用，面上項目，中國博士後基金 （主持，項目號： 2015M571495）
期刊論文（英文）
1. Jiaqiao Hu*, Meichen Song, Michael C. Fu, and Yijie Peng, “Simulation Optimization of Conditional Value-at-Risk”, IISE Transactions, accepted.
2. Xiaotian Liu, Min Hu, Yijie Peng, and Yaodong Yang, “ Multi-Agent Deep Reinforcement Learning for Multi-Echelon Inventory Management ”, Production and Operations Management, accepted.
3. Yijie Peng, Michael Fu, Jiaqiao Hu*, Pierre L’Ecuyer, and Bruno Tuffin, “Generalized Likelihood Ratio Method for Stochastic Models with Uniform Random Numbers as Inputs”, European Journal of Operational Research, 321, 493–502, 2025.
4. Xiaotian Liu, Yijie Peng*, Gongbo Zhang*, and Ruihan Zhou, “An Efficient Node Selection Policy for Monte Carlo Tree Search with Neural Networks”, INFORMS Journal on Computing, accepted.
5. Gongbo Zhang, Haobin Li, Xiaotian Liu, and Yijie Peng *, “Simulation Budget Allocation for Improving Scheduling and Routing of Automated Guided Vehicles in Warehouse Management”, Journal of the Operations Research Society of China, accepted.
6. Gongbo Zhang, Sihua Chen*, Kuihua Huang, and Yijie Peng*, “Efficient Learning for Selecting Top-m Context-Dependent Designs”, IEEE Transactions on Automation Science and Engineering, accepted.
7. Li Xiao, Zeliang Zhang, Kuihua Huang, Jinyang Jiang, and Yijie Peng*, “ Noise Optimization in Artificial Neural Networks”, IEEE Transactions on Automation Science and Engineering, accepted.
8. Jiaqiao Hu, Xiangyu Yang*, Jian-Qiang Hu, and Yijie Peng, “A Q-learning Algorithm for Markov Decision Processes with Continuous State Spaces”, Systems & Control Letters, 187, 105782, 2024.
9. Ting Gan, Luxi Qu, Shu Qu, Yuanyuan Qi, Yuemiao Zhang, Yanna Wang, Yang Li, Lijun Liu, Sufang Shi, Jicheng Lv, Hong Zhang, Yijie Peng*, and Xujie Zhou*, “ Unveiling Biomarkers and Therapeutic Targets in IgA Nephropathy Through Large- scale Blood Transcriptome Analysis”, International Immunopharmacology, 132, 111905, 2024.
10. Haidong Li, Henry Lam, and Yijie Peng*, “ Efficient Learning for Clustering and Optimizing Context-Dependent Designs”, Operations Research, 72(2), 617-638,2024.
11. Yi Zheng, Min Lei, and Yijie Peng*, “A Simulation Optimization Method for Coordination of Production, Transportation and Sales”, Fundamental Research, 2023.
12. Gongbo Zhang, Yijie Peng*, Jianghua Zhang*, and Enlu Zhou, “Asymptotically Optimal Sampling Policy for Selecting Top-m Alternatives”, INFORMS Journal on Computing, 35(6):1261-1285, 2023.
13. Lei Lei, Yijie Peng*, Michael C. Fu, and Jian-Qiang Hu, `` Copula Sensitivity Analysis for Portfolio Credit Derivatives”, European Journal of Operational Research, 308, 455-466, 2023.
14. Gongbo Zhang, Bin Chen, Qinshan Jia, and Yijie Peng*, “ Dynamic Sampling Allocation for Selecting a Subset with the Best”, IEEE Transactions on Automatic Control, 68(8), 4904-4911, 2023.
15. Bernd Heidergott, and Yijie Peng*, ``Gradient Estimation for Smooth Stopping Criteria”, Advances in Applied Probability, 55, 29-55, 2023.
16. Qinghao Wang, Yijie Peng, and Yaodong Yang, “Solving Inventory Management Problems Through Deep Reinforcement Learning”, Journal of Systems Science and Systems Engineering, 31, 677–689, 2022.
17. Jiaqiao Hu, Yijie Peng*, Gongbo Zhang, Qi Zhang, “A Stochastic Approximation Method for Simulation-based Quantile Optimization”, INFORMS Journal on Computing, 34(5), 2889-2907, 2022.
18. Haidong Li, Yijie Peng*, Xiaoyun Xu, Bend Heidergott, and Chun-Hung Chen, `` Efficient Learning for Decomposing and Optimizing Random Networks”, Fundamental Research, 2, 487–495, 2022.
19. Yijie Peng, Michael Fu, Jiaqiao Hu *, Pierre L’ Ecuyer, and Bruno Tuffin, “Variance Reduction for Generalized Likelihood Ratio Method By Conditional Monte Carlo and Randomized Quasi-Monte Carlo”, Journal of Management Science and Engineering, 7(4), 550-577, 2022.
20. Yijie Peng, Li Xiao*, Bernd Heidergott, Jeff Hong, and Henry Lam, ``A New Likelihood Ratio Method for Training Artificial Neural Networks”, INFORMS journal on Computing, 34(1), 638-655, 2022.
21. Zhongshun Shi, Yijie Peng*, Leyuan Shi, Chun-Hung Chen, and Michael C. Fu, ``Dynamic Sampling Allocation Under Finite Simulation Budget for Feasibility Determination”, INFORMS Journal on Computing, 34(1), 557-568, 2022.
22. Peter W. Glynn, Yijie Peng*, Michael C. Fu, and Jian-Qiang Hu, ``Computing Sensitivities for Distortion Risk Measures”, INFORMS Journal on Computing, 33(4), 1520-1532, 2021.
23. Haidong Li, Xiaoyun Xu*, Yijie Peng, and Chun-Hung Chen, ``Efficient Sampling for Selecting Important Nodes in Random Network”, IEEE Transactions on Automatic Control, 66(3), 1321 – 1328, 2021.
24. Yijie Peng*, Chun-Hung Chen, Michael C. Fu, Jian-Qiang Hu and Ilya O. Ryzhov, ``Efficient Sampling Allocation Procedures for Optimal Quantile Selection”, INFORMS Journal on Computing, 33(1), 230–245, 2021.
25. Yijie Peng*, Michael C. Fu, Bernd Heidergott, and Henry Lam ``Maximum Likelihood Estimation by Monte Carlo Simulation: Toward Data-Driven Stochastic Modeling”, Operations Research, 68(6), 1896–1912, 2020.
26. Zhenyu, Cui, Michael C. Fu, Yijie Peng, Lingjiong Zhu *, ``Optimal Unbiased Estimation for Expected Cumulative Discounted Cost”, European Journal of Operations Research, 286 (2), 604-618, 2020.
27. Yijie Peng, Jie Song*, Jie Xu, and Edwin K. P. Chong, `` Stochastic Control Framework for Determining Feasible Alternatives in Sampling Allocation”, IEEE Transactions on Automatic Control, 65(6), 2647 - 2653, 2020.
28. Peter W. Glynn, Lin Fan, Michael C. Fu, Jian-Qiang Hu, and Yijie Peng*, ``Technical Note---Central Limit Theorems for Estimated Functions at Estimated Points”, Operations Research, 68(5), 1557-1563, 2020.
29. Zhenyu Cui, Michael C. Fu, Jian-Qiang Hu, Yanchu Liu, Yijie Peng*, and Lingjiong Zhu, ``On the Variance Property of Single-Run Unbiased Stochastic Derivative Estimators”, INFORMS Journal on Computing, 32 (2), 390-407, 2020.
30. Joost Berkhout, Bernd Heidergott*, Henry Lam, and Yijie Peng, `` From Data to Stochastic Modeling and Decision Making: What Can We Do Better?”, Asia-Pacific Journal of Operational Research, 36(6), 1940012, 2019.
31. Yijie Peng, Edward Huang, Jie Xu, Zhongshun Shi *, and Chun-Hung Chen, ``A Coordinate Optimization Approach for Concurrent Design”, IEEE Transactions on Automatic Control, 64 (7), 2913-2920, 2019.
32. Yijie Peng*, Jie Xu, Loo-Hay Lee, Jian-Qiang Hu, and Chun-Hung Chen, ``Efficient Simulation Sampling Allocation Using Multifidelity Models”, IEEE Transactions on Automatic Control, 64 (8), 3156-3169, 2019.
33. Yijie Peng*, Chun-Hung Chen, Michael C. Fu, and Jian-Qiang Hu, ``Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario”, IEEE Transactions on Automatic Control, 63(9), 3091-3097, 2018.
34. Yijie Peng*, Edwin K.P. Chong, Chun-Hung Chen, and Michael C. Fu, ``Ranking and Selection as Stochastic Control”, IEEE Transactions on Automatic Control, 63 (8), 2359-2373, 2018.
35. Yijie Peng, Michael C. Fu, Jian-Qiang Hu* and Bernd Heidergott, ``A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters”, Operations Research, 66 (2), 487-499, 2018. (INFORMS Simulation Society Outstanding Simulation Publication Award)
36. Lei Lei*, Yijie Peng, Michael C. Fu and Jian-Qiang Hu, ``Applications of the Generalized Likelihood Ratio Method to Distribution Sensitivity and Steady-State Simulation”, Journal of Discrete Event Dynamic Systems, 28 (1), 109-125, 2018.
37. Yijie Peng* and Michael C. Fu, ``Myopic Allocation Policy with Asymptotically Optimal Sampling Rate”, IEEE Transactions on Automatic Control, 62 (4), 2041- 2047, 2017.
38. Yijie Peng, Michael C. Fu and Jian-Qiang Hu*, ``Gradient-Based Simulated Maximum LikelihoodEstimation on StochasticVolatility ModelsUsing Characteristic Functions”, Quantitative Finance, 16 (9), 1393-1411, 2016.
39. Yijie Peng*, Chun-Hung Chen, Michael C. Fu and J.Q. Hu, ``Dynamic Sampling Allocation and Design Selection’’, INFORMS Journal on Computing, 28 (2), 195-208, 2016.
40. Yijie Peng, Michael C. Fu and J.Q. Hu *, ``Gradient-Based Simulated Maximum Likelihood Estimation on Lévy Driven Ornstein-Uhlenbeck Stochastic Volatility Models’’, Quantitative Finance, 14 (8), 1399-1414, 2014.
41. Yijie Peng, Chun-Hung Chen, Michael C. Fu and J.Q. Hu *, ``Efficient Simulation Resource Sharing and Allocation for Selecting the Best’’, IEEE Transactions on Automatic Control, 58 (4), 1017 – 1023, 2013.
42. Rachel Chen, Jianqiang Hu* and Yijie Peng, ``Simulation of Lévy-driven Models and Its Application in Finance’’, Numerical Algebra, Control and Optimization, 2(4), 749-765, 2012.
會議論文（英文）
1. Jinyang Jiang, Bernd Heidergott, Jiaqiao Hu, and Yijie Peng, “ Distortion Risk Measure-based Deep Reinforcement Learning ”, Proceedings of Winter Simulation Conference, 2025.
2. Gongbo Zhang, and Yijie Peng, “Solving Mixed Integer Linear Programs by Monte Carlo Tree Search”, Proceedings of Winter Simulation Conference, 2025.
3. Zishi Zhang, Haidong Li, Ying Liu, and Yijie Peng, “ Dynamic Assortment Optimization in Live-Streaming Sales”, Proceedings of Winter Simulation Conference, 2025.
4. Ruihan Zhou, and Yijie Peng, “ Fixed-precision Ranking and Selection as Markov Decision Process”, Proceedings of Winter Simulation Conference, 2025.
5. Xinbo Shi, Bruno Tuffin, and Yijie Peng, “ Finite Budget Allocation Improvement in Ranking and Selection”, Proceedings of Winter Simulation Conference, 2025.
6. Tao Ren, Ruihan Zhou, Jinyang Jiang, Jiafeng Liang, Qinghao Wang, and Yijie Peng*, ” RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search” , ACM International Conference on AI in Finance, 2024.
7. Jinyang Jiang, Zeliang Zhang, Chenliang*, Zhaofei Yu*, and Yijie Peng*, "One Forward is Enough for Neural Network Training via Likelihood Ratio Method", Twelfth International Conference on Learning Representations (ICLR), 2024.
8. Ruihan Zhou and Yijie Peng, “POMDP-Based Ranking and Selection”, Proceedings of Winter Simulation Conference, 2023.
9. Xinbo Shi, Yijie Peng, and Gongbo Zhang, “Top-two Thompsom Sampling for Selecting Context-dependent Best”, Proceedings of Winter Simulation Conference, 2023.
10. Gongbo Zhang, Xiaotian Liu, and Yijie Peng, “A Simulation Optimization Method for Scheduling Automated Vehicles in A Stochastic Warehouse Management System”, Proceedings of Winter Simulation Conference, 2023.
11. Haidong Li, Long Wang, Yijie Peng, and DiWang, “ Efficient Bandwidth Selection for Kernel Density Estimation”, Proceedings of Winter Simulation Conference, 2023.
12. Jingyang Jiang, Jiaqiao Hu, Yijie Peng, ``Quantile-Based Policy Optimization for Reinforcement Learning’’, Proceedings of Winter Simulation Conference, 2022.
13. Gongbo Zhang, Yijie Peng, and Yilong Xu, “An Efficient Dynamic Sampling Policy for Monte Carlo Tree Search”, Proceedings of Winter Simulation Conference, 2022.
14. Yijie Peng and Gongbo Zhang, “Thompson Sampling Meets Ranking and Selection”, Proceedings of Winter Simulation Conference, 2022.
15. Lei Lei, Christos Alexopoulos, Yijie Peng, and James Wilson, “Estimating Confidence Region for Distortion Risk Measures and Their Gradients”, Proceedings of Winter Simulation Conference, 2022.
16. Li Xiao, Zeliang Zhang, Jinyang Jiang, and Yijie Peng, “Noise Optimization for Artificial Neural Networks”, Proceedings of IEEE Conference on Automation Science and Engineering, 2022.
17. Gongbo Zhang, Yijie Peng, Jianghua Zhang, and Enlu Zhou, “ Dynamic Sampling for Subset Selection Problem”, Proceedings of Winter Simulation Conference, 2021.
18. Yijie Peng, Michael Fu, Jiaqiao Hu, Pierre L’ Ecuyer, and Bruno Tuffin, “Variance Reduction for Generalized Likelihood Ratio Method in Quantile Sensitivity Estimation”, Proceedings of Winter Simulation Conference, 2021.
19. Gongbo Zhang, Yijie Peng, and Shuhuai Yang, “Gradient-Based Simulation Optimization for Economic Design of Control Charts”, Proceedings of IEEE Conference on Automation Science and Engineering, 2021.
20. Xiangyu Yang, Jiaqiao Hu, Jian-Qiang Hu, and Yijie Peng, ``Asynchronous Value Iteration for Markov Decision Process with Continuous State Space’’, Proceedings of Winter Simulation Conference, 2020.
21. Haidong Li, Henry Lam, Zhe Liang, and Yijie Peng, “Context-Dependent Ranking and Selection Under a Bayesian Framework”, Proceedings of Winter Simulation Conference, 2020.
22. Lei Lei, Christos Alexopoulos, Yijie Peng, and James Wilson, “Confidence Intervals and Confidence Regions for Quantiles Based on Conditional Monte Carlo and Generalized Likelihood Ratios”, Proceedings of Winter Simulation Conference, 2020.
23. Li Xiao, Yijie Peng *, Jeff Hong, Zewu Ke, and Shuhuai Yang, ``Training Artificial Neural Networks by Generalized Likelihood Ratio Method”, Proceedings of IEEE Conference on Automation Science and Engineering, 2020.
24. Gongbo Zhang, Chun-Hung Chen, Qing-shan Jia, and Yijie Peng, “ Dynamic Sampling Allocation for Selecting a Good Enough Alternative”, Proceedings of IEEE Conference on Automation Science and Engineering, 2020.
25. Yijie Peng, Michael C. Fu, Jian-Qiang Hu, and Lei Lei, “Estimating Quantile Sensitivity for Financial Models with Correlations and Jumps”, Proceedings of Winter Simulation Conference, 2019.
26. Haidong Li, Yijie Peng, Xiaoyun Xu, Chun-Hung Chen, and Bernd Heidergott, “Dynamic Sampling Procedure for Decomposable Random Networks”, Proceedings of Winter Simulation Conference, 2019.
27. Bowen Pang, Xiaolei Xie, Bernd Heidergott, and Yijie Peng “Optimizing Outpatient Department Staffing Level using Multi-Fidelity Models”, Proceedings of IEEE Conference on Automation Science and Engineering, 2019.
28. Nanne Dieleman, Bernd Heidergott, and Yijie Peng “ Data-Driven Fitting of the G/G/1 Queue”, Proceedings of International Conference on Service Systems and Service Management, 2019. (Best Student Paper Award)
29. Yijie Peng, Chun-Hung Chen, Edwin K.P. Chong, and Michael C. Fu, ``A Review of Static and Dynamic Optimization for Ranking and Selection”, Proceedings of Winter Simulation Conference, 2018.
30. Yijie Peng, Jie Song, Jie Xu, and Edwin K. P. Chong, ``Dynamic Sampling Allocation for Feasibility Determination”, Proceedings of IEEE Conference on Automation Science and Engineering, 2018.
31. Haidong Li, Xiaoyun Xu, Yijie Peng, and Chun-Hung Chen, `` Efficient Sampling Procedure for Selecting the Largest Stationary Probability of a Markov Chain”, Proceedings of IEEE Conference on Automation Science and Engineering, 2018.
32. Yijie Peng, Michael C. Fu, Peter W. Glynn, and Jian-Qiang Hu, ``On the Asymptotic Analysis of Quantile Sensitivity Estimation by Monte Carlo simulation”, Proceedings of Winter Simulation Conference, 2017.
33. Yijie Peng, Edward Huang, Jie Xu, and Chun-Hung Chen, ``Concurrent Engineering: An Optimization Approach for Team Coordination Through Information Sharing’’, Proceedings of IEEE Conference on Automation Science and Engineering, 2017. (Best Paper Award Finalist)
34. Yijie Peng, Michael C. Fu and Jian-Qiang Hu, ``On the Regularity Conditions and Applications for Generalized Likelihood Ratio Method”, Proceedings of Winter Simulation Conference, 2016.
35. Yijie Peng, Michael C. Fu and Jian-Qiang Hu, ``Estimating Distribution Sensitivity Using Generalized Likelihood Ratio Method”, Proceedings of IEEE International Workshop on Discrete Event Systems, 2016.
36. Yijie Peng, Chun-Hung Chen, Michael C. Fu and J.Q. Hu, `` Non-Monotonicity of Probability of Correct Selection’’, Proceedings of Winter Simulation Conference, 2015.
37. Yijie Peng, Chun-Hung Chen, Michael C. Fu and J.Q. Hu, ``A Dynamic Framework for Statistical Selection Problems’’, Proceedings of Winter Simulation Conference, 2013.
中文發表
1. 彭艷玲 ，彭一傑*，周紅利 ，汪壽陽 ，蔣遠勝 ，“基於機器學習的農戶農地經 營權抵押貸款信用風險識別及其損失度量”，《系統工程理論與實踐》，2024.
2. 李廣昊，黃魁華，楊耀東，張誠，彭一傑*，“一種基於聯邦學習的供應鏈需 求預測方法”，《工程管理科技前沿》，2024.
3. 李海東， 張路霞*，楊超，李鵬飛，彭一傑* ，“我國重大疾病跨地域就診的 隨機網路建模與分析”，《管理工程學報》，2024.
4. 王清昊，彭艷玲， 彭一傑，楊耀東*，“基於深度強化學習驅動藤 copula 方法 的農地經營權抵押貸款風險變數關聯結構分析”，《計量經濟學報》，2023.
5. 張公伯，李海東，彭一傑*，“隨機梯度估計及其在製造中的套用”，《系統管 理學報》，2022.
6. 張公伯，彭一傑*，楊書淮，“控制圖經濟設計的隨機梯度最佳化方法”，《工程 管理科技前沿》, 3, 41(3), 2022.
7. 鮑錦濤 ，鄭 毅 ，彭一傑 ，趙英弘 ，郝紅全 ，鄭知敏*，“原創性基礎研究的內涵分析及對原創探索計畫項目的啟示” ，《中國科學院院刊》，37(3) ，384-394， 2022.
8. 陳睿迪，彭一傑，胡建強*，``金融中的 Lévy 模型及其仿真’’，《運籌學學報》， 13 (1) ，1-9，2013.
學術活動
協會成員：INFORMS 、IEEE 會員，中國運籌協會會員，北京運籌學會副理事長、 全國工業統計學教學研究會金融科技與大數據分會副理事長、管理科學與工程 協會人工智慧技術與管理套用分會副理事長、管理科學與工程協會理事
期刊與會議編輯：Journal of System Science and System Engineering 部門主編， 《系統管理學報》領域編委， Asia-Pacific Journal of Operational Research 、 Journal of Systems Science and Information 副主編 ，Proceedings Editor of 2022 Winter Simulation Conference
專利
發明創造名稱：一種預訓練模型微調方法及系統 ，發明人：江金陽,彭一傑,張澤良, 張誠,李廣昊，專利號： 202410247177.5
