雷金龙，理学博士，同济大学“青年百人A”教授，国家海外高层次青年人才计划获得者。2011年于中国科学技术大学获得学士学位，2016年于中国科学院数学与系统科学研究院获得理学博士学位。 2016- 2019年在美国宾夕法尼亚州立大学从事博士后研究。研究方向是不确定信息下的多智能体优化与非合作博弈理论与方法，及其在智能无人集群系统中的应用。获得中国科协青年人才托举工程、第27届“关肇直”奖、上海市青年科技英才“扬帆计划”并主持国家自然科学基金委青年基金和面上基金项目等，并参与上海市市级科技重大专项等。已发表50余篇期刊和会议论文，包括优化控制与运筹学顶刊IEEE Trans. Automatic Control、SIAM J. Optimization、Operations Research和 Mathematics of Operations Research及人工智能顶会NeurIPS等。代表性论文如下：
l Yang Lv, Jinlong Lei∗, and Peng Yi, “A Local Information Aggregation based Multi-Agent Reinforcement Learning for Robot Swarm Dynamic Task Allocation", IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 6, pp. 10437–10449, June 2025.
l Yue Pan, Jinlong Lei∗, Peng Yi, Lulu Guo, and Hong Chen, “Towards Cooperative Driving among Heterogeneous CAVs: A Safe Multi-Agent Reinforcement Learning Approach", IEEE Transactions on Intelligent Vehicles, 10.1109/TIV.2024.3450205, August 2024.
l Jinlong Lei and Uday V. Shanbhag, “Variance-Reduced Accelerated First-order Methods: Central Limit Theorems and Confidence Statements", Mathematics of Operations Research, June 2024, https://doi.org/10.1287/moor.2021.0068.
l Shijie Huang, Jinlong Lei, Yiguang Hong∗, Uday V. Shanbhag, and Jie Chen, “No-regret distributed learning in subnetwork zero-sum games", IEEE Transactions on Automatic Control, vol. 69, no.10, pp. 6620– 6635, October 2024.
l Wenting Liu, Jinlong Lei, and Peng Yi∗, “No-regret learning for repeated non-cooperative games with lossy bandits", Automatica, Regular Paper, vol. 160, Feb 2024, 111455.
l Shijie Huang, Jinlong Lei∗, Yiguang Hong, “A Linearly Convergent Distributed Nash Equilibrium Seeking algorithm for Aggregative Games", IEEE Transactions on Automatic Control, vol.68, no.3, pp. 1753–1759, March 2023.
l Xianlin Zeng, Jinlong Lei∗, and Jie Chen, “Dynamical Primal-Dual Accelerated Method with Applications to Network Optimization", IEEE Transactions on Automatic Control, vol.68, no.3, pp. 1760–1767, March 2023.
l Jinlong Lei and Uday V. Shanbhag, "Distributed Variable Sample-Size Gradient-response and Best-response Schemes for Stochastic Nash Games over Graphs", SIAM Journal on Optimization, pp. 573–603, vol. 32, no. 2, 2022.
l Jinlong Lei and Uday V. Shanbhag, “Stochastic Nash Equilibrium Problems: Models, Analysis, and Algorithms", IEEE Control Systems Magazine, vol. 42, no. 4, pp. 103–124, 2022.
l Peng Yi, Jinlong Lei∗, Yiguang Hong, Jie Chen, and Guodong Shi, “Distributed Linear Equations over Random Networks", IEEE Transactions on Automatic Control, vol. 68, no. 4, pp. 2607-2614, April 2023.
l Jinlong Lei, Peng Yi∗, Jie Chen, and Yiguang Hong, “Distributed Variable Sample-size Stochastic Optimization with Fixed Step-sizes", IEEE Transactions on Automatic Control, pp. 5630–5637, vol. 67, no. 10, 2022.
l Jinlong Lei and Uday V. Shanbhag, "Asynchronous Schemes for Stochastic and Misspecified Potential Games and Nonconvex Optimization," Operations Research, vol. 68, no. 6, pp. 1742–1766, 2020.
l Jinlong Lei, Uday V. Shanbhag, Jong-Shi Pang, and Suvrajeet Sen, “On Synchronous, Asynchronous, and Randomized Best-Response schemes for computing equilibria in Stochastic Nash games,” Mathematics of Operations Research, vol. 45, no.1, pp. 157-190, 2020.
l Jinlong Lei and Uday V. Shanbhag, “Asynchronous variance-reduced block schemes for composite non-convex stochastic optimization: block-specific steplengths and adapted batch-sizes", Optimization Methods and Software, vol. 37, no. 1, pp. 264–294, 2022.
l Jinlong Lei, and Han-Fu Chen, "Distributed Stochastic Approximation Algorithm With Expanding Truncations: Algorithm and Applications", IEEE Transactions on Automatic Control, vol. 65, no. 2, pp. 664-679, Full Paper, 2020.
l Jinlong Lei, Peng Yi, Guodong Shi, and Brian D. O. Anderson, ``Distributed Algorithms with Finite Data Rates that Solve Linear Equations", SIAM Journal on Optimization, vol. 30, no. 2, pp.1191–1222, 2020.
l Jinlong Lei, Peng Yi, Yiguang Hong, Jie Chen, and Guodong Shi, “Online Convex Optimization Over Erdos-Renyi Random Networks", Advances in Neural Information Processing Systems, 2020.
l Jinlong Lei, Han-Fu Chen, and Hai-Tao Fang, "Asymptotic Properties of Primal-Dual Algorithm for Distributed Stochastic Optimization Over Random Networks," SIAM Journal on Control and Optimization, vol. 56, no.3, pp. 2159--2188, 2018.
l Jinlong Lei, Han-Fu Chen, and Hai-Tao Fang, "Primal-Dual Algorithm for Constrained Network Optimization", Systems and Control Letters, vol. 96, pp. 110--117, 2016.
l Jinlong Lei and Han-Fu Chen, "Stochastic Approximation Based Distributed Randomized Page Rank Algorithm", IEEE Transactions on Automatic Control, vol. 60, no. 6, pp. 1641-1646, 2015
近五年主持的科研项目：
（1） 国家自然科学基金委员会, 面上项目, 72271187, 基于博弈方法的有人-无人混合复杂系统建模和决策, 2023-01-01 至 2026-12-31, 在研, 主持，47万，国家级。
（2）国家自然科学基金委员会, 青年科学基金项目, 62003240, 基于变样本采样的多智能体分布式随机优化算法研究, 2021-01-01 至 2023-12-31, 结题, 主持，24万，国家级。
（3）上海市科学技术委员会, 青年科技英才“扬帆计划”, 20YF1452800, 网络资源约束下的分布式机器学习方法, 2020-07 至 2023-06, 结题, 主持，20万，省部级。
（4）中国科学技术协会, 中国科协“青年人才”托举工程, 2019QNRC001, 第五届青年托举人才, 2019-01至 2021-12, 结题, 主持，45万，省部级。
发明专利：
l 网络化系统机器学习中自适应高效通信机制的设计与优化，衣鹏,洪奕光,雷金龙,陈杰,李莉,梁舒,马晓宇， CN 113300890 A，2022-06-14。
l 一种网络化机器学习系统的自适应稀疏度量化方法，衣鹏,洪奕光,雷金龙,李莉,陈杰,梁舒,李修贤,马晓宇，CN 113159331 A，2023-06-30。
讲授本科课程：随机过程、《专业导论（信息与智能网联类）》
实验室网站：https://aigame.tongji.edu.cn/
