宁超

职称:长聘教轨副教授

邮箱:chao.ning@sjtu.edu.cn

地址:电信群楼 2-400

招生信息

导师信息:宁超,博士生导师,国家高层次青年人才,上海市领军人才,上海市浦江人才,小米青年学者


  1. 博士生、硕士生:欢迎计划明年入学的同学提前联系
  2. 博士后:欢迎随时联系
  3. 本科生:长期接收未来准备出国、希望本科阶段发表论文的同学加入课题组进行研究、做毕业设计。表现优秀者可推荐至国外名校

教育经历

2020年8月,美国康奈尔大学(Cornell University),博士学位

2015年7月,清华大学,硕士学位

2012年7月,电子科技大学,学士学位

工作经历

2024年1月-至今,上海交通大学自动化系,长聘教规副教授

2021年2月-2023年12月,上海交通大学自动化系,助理教授

2020年8月-2021年1月,美国康奈尔大学,博士后

科研方向

  1. 人工智能驱动的决策与控制科学(AI for Decision & Control Science)
  2. 数据驱动的不确定性优化
  3. 基于学习的模型预测控制
  4. 大数据解析,深度学习,人工智能
  5. 综合能源系统
  6. 化工过程系统工程

科研项目

  1. 国家自然科学基金优青项目(海外)
  2. 上海市浦江人才计划项目 A类
  3. 国家自然科学基金青年项目
  4. 能源化工过程智能制造教育部重点实验室开放课题
  5. 上海交通大学回国人员科研启动经费项目

荣誉与奖励

  1. 国家高层次青年人才计划
  2. 上海市领军人才计划
  3. 上海市浦江人才计划 A类 (2021年)
  4. 小米青年学者项目
  5. 美国控制会议(ACC)最佳论文奖 (2020年 O. Hugo Schuck Award)
  6. 国际工业人工智能会议 (IAI)  Best Paper Award (2022年)
  7. IEEE 国际电力与能源会议 Best Paper Award (2022年)
  8. 美国化工协会(AIChE)可持续工程(Sustainable Engineering)最佳学生论文奖 (2019年)
  9. 美国自然科学基金(NSF)Travel Grant(2017年)
  10. 康奈尔大学全额奖学金
  11. 清华大学优秀毕业生(2015年)
  12. 北京市优秀毕业生(2015年)
  13. 清华大学优秀硕士毕业论文(2015年)
  14. 国家奖学金(2009, 2010, 2011, 2014年
  15. 全国大学生数学建模竞赛全国一等奖 (2010年)

科研成果

期刊论文

[1] Ma, X., Ning, C.* (通讯作者), Li, L., Qiu, H., Gu, W., and Dong, Z. (2024). Bayesian Nonparametric Two-Stage Distributionally Robust Unit Commitment Optimization: From Global Multimodality to Local Trimming-Wasserstein Ambiguity. IEEE Transactions on Power Systems. DOI: 10.1109/TPWRS.2024.3350632.

[2] Li, L., Ning, C.*(通讯作者), Qiu, H., Du, W., and Dong, Z. (2023). Online Data-Stream-Driven Distributionally Robust Optimal Energy Management for Hydrogen-Based Multi-Microgrids. IEEE Transactions on Industrial Informatics. DOI: 10.1109/TII.2023.3316176.

[3] Ning, C.* (通讯作者), Ma, X. (2023). Data-Driven Bayesian Nonparametric Wasserstein Distributionally Robust Optimization. IEEE Control Systems Letters, 7, 3597-3602.

[4] Ning, C., You, F. (2022). Deep Learning based Distributionally Robust Joint Chance Constrained Economic Dispatch under Wind Power Uncertainty. IEEE Transactions on Power Systems37191-203.

[5] Ning, C., You, F. (2021). Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems. Automatica, 125, 109402.

[6] Ning, C., You, F. (2020). A Transformation-Proximal Bundle Algorithm for Multistage Adaptive Robust Optimization and Application to Constrained Robust Optimal Control. Automatica, 113, 108802.

[7] Ning, C., You, F. (2019). Data-Driven Adaptive Robust Unit Commitment under Wind Power Uncertainty: A Bayesian Nonparametric Approach. IEEE Transactions on Power Systems, 34, 2409-2418.

[8] Ning, C., You, F. (2017). Data-Driven Adaptive Nested Robust Optimization: General Modeling Framework and Efficient Computational Algorithm for Decision Making under Uncertainty. AIChE Journal, 63, 3790-3817.

[9] Ning, C., You, F. (2017). A Data-Driven Multistage Adaptive Robust Optimization Framework for Planning and Scheduling under Uncertainty. AIChE Journal, 63, 4343-4369.

[10] Ning, C., You, F. (2019). Optimization under Uncertainty in the Era of Big Data and Deep Learning: When Machine Learning Meets Mathematical Programming. Computers & Chemical Engineering, 125, 434-448. (Review Paper)

[11] Ning, C., You, F. (2019). Data-Driven Wasserstein Distributionally Robust Optimization for Biomass with Agricultural Waste-to-Energy Network Design under Uncertainty. Applied Energy, 255, 113857.

[12] Ning, C., Chen, M., Zhou, D. (2014) Hidden Markov Model-Based Statistics Pattern Analysis for Multimode Process Monitoring: An Index-Switching Scheme. Industrial & Engineering Chemistry Research, 53, 11084-11095.

[13] Ning, C., You, F. (2018). Data-Driven Stochastic Robust Optimization: General Computational Framework and Algorithm Leveraging Machine Learning for Optimization under Uncertainty in the Big Data Era. Computers & Chemical Engineering, 111, 115-133.

[14] Ning, C., You, F. (2018). Data-Driven Decision Making under Uncertainty Integrating Robust Optimization with Principal Component Analysis and Kernel Smoothing Methods. Computers & Chemical Engineering, 112, 190-210.

[15] Ning, C., You, F. (2018). Adaptive Robust Optimization with Minimax Regret Criterion: Multiobjective Optimization Framework and Computational Algorithm for Planning and Scheduling under Uncertainty. Computers & Chemical Engineering, 108, 425-447.

[16] Qiu, H., Gu, W., Ning, C., Lu, X., Liu, P., Wu, Z. (2023). Multistage Mixed-Integer Robust Optimization for Power Grid Scheduling: An Efficient Reformulation Algorithm. IEEE Transactions on Sustainable Energy, 14 (1), 254-271.

[17] Qiu, H., Wang, L., Gu, W., Pan, G., Ning, C., Wu, Z., Sun, Q. (2022). Multistage Scheduling of Regional Power Grids Against Sequential Outage and Power Uncertainties. IEEE Transactions on Smart Grid, 13 (6), 4624-4637.

[18] Deng, H., Yang, B., Ning, C., Chen, C. and Guan, X. (2023). Distributionally Robust Day-Ahead Scheduling for Power-Traffic Network under A Potential Game Framework. International Journal of Electrical Power & Energy Systems, 147, p.108851.

[19] Cao, J., Yang, B., Zhu, S., Ning, C., Guan, X. (2021). Day-ahead Chance-Constrained Energy Management of Energy Hub: A Distributionally Robust Approach. CSEE Journal of Power and Energy Systems.

[20] Gao, J., Ning, C., You, F. (2019). Data-Driven Distributionally Robust Optimization for Shale Gas Supply Chain Design and Operations under Uncertainty. AIChE Journal, 3, 947-963.

[21] Zhao, L., Ning, C., You, F. (2019). Operational Optimization of Industrial Steam Systems under Uncertainty Using Data-Driven Adaptive Robust Optimization. AIChE Journal, 65, e16500.

[22] Nicoletti, J., Ning, C., You, F. (2019). Incorporating Agricultural Waste-to-Energy Pathways into Biomass Product and Process Network through Data-Driven Nonlinear Adaptive Robust Optimization. Energy, 180, 556-571.


会议论文

[1] Ning, C., You, F. (2019). Data-Driven Adaptive Robust Optimization Framework for Unit Commitment under Renewable Energy Generation Uncertainty. American Control Conference (ACC), 4734-4739. (美国控制会议 ACC 最佳论文奖

[2] Li, L., Ning, C.* (2022). Integrated Power and Hydrogen Trading in Multi-microgrid Coupled with Offsite Hydrogen Refueling Stations. IEEE Conference on Energy Internet and Energy System Integration (IEEE EI2), (Accepted).

[3] Ning, C., Li, L. (2022). Online Learning Enabled Hierarchical Distributionally Robust Model Predictive Control of Green-Hydrogen Microgrids under Uncertainties. IEEE International Electrical and Energy Conference, 2366-2371. (最佳论文奖).

[4] Li, L., Ning, C.*, Qiu H. (2022). Streaming-Data-Driven Distributionally Robust Joint Operation of Multi-Microgrids and Off-Site Hydrogen Refueling Stations under Uncertainties. IEEE International Conference on Innovative Smart Grid Technologies (IEEE ISGT-Asia).

[5] Ning, C., Li, L. (2022). Data-Driven Robust Optimization for Energy Chemical Processes under Uncertainties: A Review and Tutorial. International Conference on Industrial Artificial Intelligence (IAI). (最佳论文奖).

[6] Li, L., Ning, C.* (2022). Event-Triggered Online Learning Assisted Distributionally Robust Energy Management of Ammonia-Based Multi-Energy Microgrids. International Conference on Industrial Artificial Intelligence (IAI), (Accepted).

[7] Ning, C., You, F. (2021). Data-Driven Ambiguous Joint Chance Constrained Economic Dispatch with Correlated Wind Power Uncertainty. American Control Conference (ACC), 1807-1812.

[8] Ning, C., You, F. (2019). A Transformation-Proximal Bundle Algorithm for Solving Multistage Adaptive Robust Optimization Problems. 57th IEEE Conference on Decision and Control (CDC), 2018, 2439-2444.

[9] Ning, C., Chen, M., Zhou, D. (2015) Sparse Contribution Plot for Fault Diagnosis of Multimodal Chemical Process. IFAC-PaperOnline, 48 (21), 619-626.

[10] Ning, C., You, F. (2018). Data-Driven Adaptive Robust Optimization Framework Based on Principal Component Analysis. American Control Conference (ACC), 3020-3025.

[11] Ning, C., You, F. (2019). Chemical Process Scheduling under Disjunctive Uncertainty Using Data-Driven Multistage Adaptive Robust Optimization. American Control Conference (ACC), 2145-2150.

[12] Ning, C., You, F. (2016). Data-Driven Robust MILP Model for Scheduling of Multipurpose Batch Processes under Uncertainty. 55th IEEE Conference on Decision and Control (CDC), 2016, 6180-6185.

[13] Ning, C., You, F. (2017). Leveraging Big Data for Adaptive Robust Optimization of Scheduling under Uncertainty. American Control Conference (ACC), 3783-3788.


发明专利

[1] 周东华,宁超,陈茂银. 基于稀疏贡献图的高炉多工况故障分离方法及系统. 中国发明专利 201410418264.9

[2] 周东华,宁超,陈茂银. 一种基于协方差矩阵范数逼近的多重故障重构方法. 中国发明专利 201310662933.2

[3] 周东华,宁超,陈茂银. 一种基于监控指标切换的多工况过程监控方法. 中国发明专利 201310675045.4

教授课程

AU 7032 Advanced Mathematical Optimization (英文授课)

AU 3302 Automatic Control Theory (A) (英文授课)

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