上海交通大学安泰经济与管理学院 - 教师个人主页

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葛冬冬

系别：数据与商务智能系
办公电话： 52301361
职称：教授
电子邮箱：ddge@sjtu.edu.cn

教师简介

上海交通大学智能计算研究院院长、数据与商务智能系特聘教授。目前主持国家自然科学基金杰出青年项目，重大项目。曾主持国家自然科学基金原创探索项目等。负责数学规划开源求解器LEAVES，及数学规划专业求解器COPT的开发。也负责上海市数学优化算法技术创新中心、上海市求解器自主研发与产业应用协同创新中心，上海数学与交叉学科研究院人工智能中心建设。
研究方向：超大规模数学优化问题的理论、算法与软件研发，及其在供应链、制造、交通、能源、量子计算等领域的应用。1，LP，MILP，SDP，SOCP等问题的算法理论分析与软件开发；2，基于GPU的新一代数学规划算法设计以及类CUDA数值计算库函数建设；3，大模型训练推理中的算法优化，及决策大模型的训练与应用。
我们在安泰经管学院和人工智能学院均有硕士、博士和博士后招生，欢迎在人工智能或数学规划领域有着强烈科研兴趣，且学术背景和学术训练优秀的同学跟我们联系。（请务必仔细阅读我的科研论文，确认兴趣对口，泛泛套瓷恕不回信。）
同时，我们非常注重本科生科研培养，过去十年已有近100位来自清北华五、上财、海外多高校的本科同学在我们指导下进行科研，并到多所世界名校读博，已有近30位已经毕业，在Columbia，NYU，UCL，HKU，复旦等名校任教。欢迎有志于数学优化、人工智能、管理科学等方向研究，本科期间成绩卓越的同学联系我们进行科研工作。
教育经历:
2004-08 至 2009-08, 斯坦福大学, 管理科学与工程, 博士
1999-08 至 2004-07, 纽约州立大学石溪分校, 数学，计算机，硕士
1995-07 至 1999-07, 南开大学, 数学, 学士
工作经历:
2024至今, 上海交通大学, 安泰经济与管理学院, 特聘教授；智能计算研究院，院长
2013-2023，上海财经大学, 信息管理与工程学院, 教授；交叉科学研究院，院长
2009-2013, 上海交通大学, 安泰经济与管理学院, 讲师，副教授

科学研究

近期论文（2021-今）：
1. Reward Learning From Preference With Ties, J Liu, D Ge, R Zhu, Submitted to AAAI 2025. arXiv preprint arXiv:2410.05328,2024
2. Dispatching Automated Guided Vehicles Using Efficient Data-Driven Optimization. H Qin, X Zhao, J Liu, D Ge, R Zhu. Submitted to MSOM. Available at SSRN 4959037, 2024
3. Early Birds versus Last-Minute Arrivals: Empirical Evidence and Theoretical Analysis of Arrival Time Queueing Game，X Zhao, Y Ding, D Ge, X Xie，Submitted to MSOM. Available at SSRN 4955803，2024
4. Solving Integrated Process Planning and Scheduling Problem via Graph Neural Network Based Deep Reinforcement Learning，H Li, H Zhang, Z He, Y Jia, B Jiang, X Huang, D Ge，Submitted to AAAI 2025. arXiv preprint arXiv:2409.00968，2024
5.    Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU，Q Han, Z Lin, H Liu, C Chen, Q Deng, D Ge, Y Ye，arXiv preprint arXiv:2407.15049，2024
6.    An enhanced alternating direction method of multipliers-based interior point method for linear and conic optimization，Q Deng, Q Feng, W Gao, D Ge, B Jiang, Y Jiang, J Liu, T Liu, C Xue, Y Ye, C zhang，INFORMS Journal on Computing，2024
7.    ORLM: Training Large Language Models for Optimization Modeling，Z Tang, C Huang, X Zheng, S Hu, Z Wang, D Ge, B Wang，Submitted to OR. arXiv preprint arXiv:2405.17743，2024
8.    Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming，Y Huang, W Zhang, H Li, W Xue, D Ge, H Liu, Y Ye，Submitted to IJOC. arXiv preprint arXiv:2405.16160，2024
9.    Sketched Newton Value Iteration for Large-Scale Markov Decision Processes，J Liu, C Xie, Q Deng, D Ge, Y Ye，Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), AAAI 2024, 2024
10.    Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness，C Xie, C Li, C Zhang, Q Deng, D Ge, Y Ye，The 38th Annual AAAI Conference on Artificial Intelligence AAAI 2024，2024
11.    Learning to Pivot as a Smart Expert，T Liu, S Pu, D Ge, Y Ye，The 38th Annual AAAI Conference on Artificial Intelligence AAAI 2024，2024
12.  A Low-Rank ADMM Splitting Approach for Semidefinite Programming，Q Han, C Li, Z Lin, C Chen, Q Deng, D Ge, H Liu, Y Ye，Major Revision on IJOC. arXiv preprint arXiv:2403.09133，2024
13.  Decoupling Learning and Decision-Making: Breaking the Barrier in Online Resource Allocation with First-Order Methods，W Gao, C Sun, C Xue, D Ge, Y Ye，arXiv preprint arXiv:2402.07108，2024
14.  Nonlinear modeling and interior point algorithm for the material flow optimization in petroleum refinery，F Dong, D Ge, L Yang, Z Wei, S Guo, H Xu，Electronic Research Archive 32 (2), 915-927，2024
15.  A Homogenization Approach for Gradient-Dominated Stochastic Optimization，J Tan, C Xue, C Zhang, Q Deng, D Ge, Y Ye，The Conference on Uncertainty in Artificial Intelligence UAI 2024，2024
16.  cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language，H Lu, J Yang, H Hu, Q Huangfu, J Liu, T Liu, Y Ye, C Zhang, D Ge，arXiv preprint arXiv:2312.14832，2023
17.  A Universal Trust-Region Method for Convex and Nonconvex Optimization，Y Jiang, C He, C Zhang, D Ge, B Jiang, Y Ye，arXiv preprint arXiv:2311.11489，2023
18.  Solving Linear Programs with Fast Online Learning Algorithms，W Gao, D Ge, C Sun, Y Ye. ICML'23: Proceedings of the 40th International Conference on Machine Learning，2023
19. A Homogeneous Second-Order Descent Method for Nonconvex Optimization. Chuwen Zhang, Dongdong Ge, Chang He, Bo Jiang, Yuntian Jiang, Chenyu Xue, Yinyu Ye, Major Revision on Mathematics of Operations Research. 2023
20.  Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods，C He, Y Jiang, C Zhang, D Ge, B Jiang, Y Ye. Major Revision on Mathematical Programming. arXiv preprint arXiv:2306.17516，2023
21.  Pre-trained Mixed Integer Optimization through Multi-variable Cardinality Branching，Y Chen, W Gao, D Ge, Y Ye，arXiv preprint arXiv:2305.12352，2023
22.  Stochastic Dimension-reduced Second-order Methods for Policy Optimization，J Liu, C Xie, Q Deng, D Ge, Y Ye，arXiv preprint arXiv:2301.12174，2023
23.  SOLNP+: A Derivative-Free Solver for Constrained Nonlinear Optimization，D Ge, T Liu, J Liu, J Tan, Y Ye，ACM Transactions on Mathematical Software, Accepted, 2024. arXiv preprint arXiv:2210.07160.
24.  Cardinal Optimizer (COPT) user guide，D Ge, Q Huangfu, Z Wang, J Wu, Y Ye，arXiv preprint arXiv:2208.14314，2022
25.  Bayesian dynamic learning and pricing with strategic customers，X Chen, J Gao, D Ge, Z Wang，Production and Operations Management 31 (8), 3125-3142，2022
26.  DRSOM: A Dimension Reduced Second-Order Method，C Zhang, D Ge, C He, B Jiang, Y Jiang, Y Ye，arXiv preprint arXiv:2208.00208，2022
27.  Randomized Branching Strategy in Solving SCUC Model，R Cao, Y Chen, W Gao, J Gao, Y Zhang, C Lu, D Ge，2022 4th International Conference on Power and Energy Technology，ICPET 2022
28.  Hdsdp: Software for semidefinite programming，W Gao, D Ge, Y Ye，Minor Revision on ACM Transactions on Mathematical Software. arXiv preprint arXiv:2207.13862，2022
29.  Optimization and operations research in mitigation of a pandemic，CH Chen, YH Du, DD Ge, L Lei, YY Ye，Journal of the Operations Research Society of China 10 (2), 289-304，2022
30.  JD. com: Operations research algorithms drive intelligent warehouse robots to work，H Qin, J Xiao, D Ge, L Xin, J Gao, S He, H Hu, JG Carlsson，INFORMS Journal on Applied Analytics 52 (1), 42-55，2022
31.  Uncertainty quantification for demand prediction in contextual dynamic pricing，Y Wang, X Chen, X Chang, D Ge，Production and Operations Management 30 (6), 1703-1717，2021
32.  From an interior point to a corner point: smart crossover，D Ge, C Wang, Z Xiong, Y Ye，Minor Revision on IJOC. arXiv preprint arXiv:2102.09420，2021
33.  A Gradient Descent Method for Estimating the Markov Chain Choice Model，L Fu, DD Ge，Journal of the Operations Research Society of China, 1-11，2021

数学优化软件开发：
1，Cardinal Optimizer(COPT): 领导了国内首个专业数学优化软件开发，目前有线性规划、整数规划、半定规划、二阶锥规划、二阶凸规划、混合整数二阶锥规划、混合整数半正定规划等模块，均在第三方测试榜单上排名世界前二，具体信息请参见：http://plato.asu.edu/bench.html, https://shanshu.ai/solver, 以及 Cardinal Optimizer (COPT) User Guide 2022, https://arxiv.org/abs/2208.14314
2，LEAVES mathematical programming solver: 国内首个开源数学规划软件，2016年发布，包括了线性规划、几何规划等模块。
基金：
主持国家自然科学基金的原创探索，杰出青年，重大基金等项目。

主讲课程