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，IEEE Senior Member

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

研究生培养：马徐韬（国家奖学金）

                    汪   涵（国家奖学金）

                    李龙艳（小米奖学金）

培养学生毕业去向：哈佛大学 Harvard 博士全奖、美国加州大学伯克利分校 UC Berkeley EECS 博士全奖

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

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

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. 氢能与储能
6. 绿电-氢-化工耦合系统
7. 综合能源系统
8. 化工过程系统工程

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

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）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）

期刊论文

[1] Ma, X., Ning, C.*, Du, W., Shi, Y. (2025). Data-Driven Distributionally Robust Mixed-Integer Control through Lifted Control Policy. IEEE Transactions on Automatic Control. (Accepted)

[2] Li, L., Ning, C.*, Pan, G., Zhang, L., Gu, W., Zhao L., Du, W., Shahidehpour, M. (2025). A Risk-Averse Just-In-Time Scheme for Learning Based Operation of Microgrids with Coupled Electricity-Hydrogen-Ammonia under Uncertainties. IEEE Transactions on Sustainable Energy,  (Accepted)

[3] Ning, C.*, Zhao, J., Wang, H. (2025). Learning-Enabled Stochastic Predictive Control for Nonlinear Discrete-Time Step Backward High-Order Fully Actuated Systems. International Journal of Systems Science, 1-16.

[4] Ma, X., Ning, C.*, 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, 39, 6702-6715.

[5] Li, L., Ning, C.*, Qiu, H., Du, W., Dong, Z. (2024). Online Data-Stream-Driven Distributionally Robust Optimal Energy Management for Hydrogen-Based Multi-Microgrids. IEEE Transactions on Industrial Informatics, 20, 4370-4384.

[6] Li, L., Liu, S., Ning, C.* (2025). Data-Driven Distributionally Robust Planning of Electricity-Heat-Hydrogen-Ammonia Microgrid Considering The Electrothermal-Aging Effect of SOEC. Power System Technology, 49(1), 22-31. (in Chinese)

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

[8] Ning, C., You, F. (2022). Deep Learning based Distributionally Robust Joint Chance Constrained Economic Dispatch under Wind Power Uncertainty. IEEE Transactions on Power Systems, 37, 191-203.

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

[10] 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.

[11] 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. （🏆 AIChE 可持续工程学生论文奖）

[12] 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.

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

[14] 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)

[15] 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.

[16] 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.

[17] 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.

[18] 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.

[19] 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.

[20] 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.

[21] 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.

[22] 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.

[23] 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.

[24] 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.

[25] 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.

[26] 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.

[27] Qiu, H., Veerasamy, V., Ning, C., Sun, Q., Gooi, H.B. (2024). Two-Stage Robust Optimization for Assessment of PV Hosting Capacity Based on Decision-Dependent Uncertainty. Journal of Modern Power Systems and Clean Energy. DOI: 10.35833/MPCE.2023.000488

[28] Gao, F., Yang, B., Ning, C., Guan, X. (2025). Virtual Leader-follower based Platooning Under Mixed Traffic: A Data-driven Distributionally Robust MPC Method. IEEE Transactions on Vehicular Technology. DOI: 10.1109/TVT.2025.3561126

会议论文

[1] Ma, X., Ning, C.*, Du, W. (2024). Differentiable Distributionally Robust Optimization Layers. International Conference on Machine Learning (ICML). (Top conference in AI, CCF-A)

[2] Wang, H., Ning, C.*, Li, L., Zhang, W. (2024). Online-Learning-Based Distributionally Robust Motion Control with Collision Avoidance for Mobile Robots. IEEE International Conference on Robotics and Automation (ICRA). (CAAI-A)

[3] 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 O. Hugo Schuck 最佳论文奖）

[4] Wang, H., Ning, C.* (2024). Online-Learning-Enabled Distributionally Robust Motion Control Via Uncertainty Propagation and Ambiguity Set Compression. 63rd IEEE Conference on Decision and Control (CDC).(Accepted).

[5] Liu, S., Li, L., Ning, C.* (2024). Optimal Planning of Multi-Energy Systems for Sustainable Ammonia Production Considering Electrothermal-Aging Effect of SOEC. IEEE 22nd International Conference on Industrial Informatics (IEEE INDIN).

[6] 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).

[7] 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（CIEEC）, 2366-2371. (🏆 最佳论文奖).

[8] 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).

[9] 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).

[10] 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).

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

[12] 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.

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

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

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

[16] 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.

[17] 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] 宁超，李龙艳，刘淑娴，基于多阶段分布鲁棒优化的混合电氢交通站规划方法及系统, 2025-1-6, 中国, 2025100155867 (发明专利)

[2] 宁超，李龙艳，顾峻豪，考虑混合电解槽的离网氨氢微网规划方法、系统及介质, 2024-9-26, 中国, 202411348545.1 (发明专利)

[3] 宁超，赵珺豪，汪涵，基于学习和全驱系统的PEM电解槽温度预测控制方法和设备, 2024-9-24, 中国, 202411328268.8 (发明专利)

[4] 宁超，李龙艳，刘淑娴，一种考虑SOEC电热老化效应的电-热-氢-氨耦合微网规划方法，2024-8-7，中国，202411078365.6 (发明专利)

[5] 宁超，马翱凯，马徐韬，李龙艳，一种数据驱动的电-氢综合能源系统多阶段分布鲁棒调度方法，2024-4-23，中国，2024104906930 (发明专利)

[6] 宁超，马徐韬，李龙艳，数据驱动的非参数贝叶斯分布鲁棒机组组合优化方法, 2023-10-27, 中国，2023114096969 (发明专利)

[8] 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

[9] 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

[10] 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

AU 7032 Advanced Mathematical Optimization （英文授课）

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

1. 中国自动化学会

2. 中国可再生能源学会（氢能专委会）

3. 中国节能协会（氢能专委会）

4. 中国系统工程学会（过程系统工程专委会）

5. 中国电机工程学会

6. 中国电工技术学会（高级会员）

7. IEEE（高级会员）