北京交通大学硕士研究生导师信息:周声龙

2026-04-22 22:24:00来源: 网络

  在读研期间,所有与你读研相关的事情,可能都需要经过你的导师同意,所以说,选择导师真的很重要,也希望大家能够认真对待这件事,怎样才能选择适合自己的导师呢?这就要我们提前做足功课,尽可能多的搜集有关你准备报考的导师的信息,下面新东方在线考研频道为大家分享:“北京交通大学硕士研究生导师信息:周声龙”文章。

  周声龙

  博士 、教授

  基本信息

  办公电话:电子邮件: shlzhou@bjtu.edu.cn

  通讯地址:北京市海淀区北下关北京交通大学科技大厦10B11邮编:100044

  研究兴趣

  最优化(包括稀疏阶跃与分布式优化)理论与算法,以及在人工智能、机器学习、信号处理等领域中的应用

  详见个人主页:https://shenglongzhou.github.io/

  招生专业

  数学博士和硕士

  欢迎对最优化理论与算法、人工智能、机器学习、信号处理等领域感兴趣的学生申请

  教育背景

  2014-10 至 2018-12,博士,英国南安普顿大学,运筹学

  2011-09 至 2014-03,硕士,北京交通大学,运筹学与控制论

  2007-09 至 2011-06,学士,北京交通大学, 信息与计算科学

  工作经历

  2023-03 至今, 北京交通大学,数学与统计学院,教授

  2021-06 至 2023-03,伦敦帝国理工学院,工程学院,副研究员

  2020-02 至 2021-02,英国南安普顿大学,数学学院,讲师

  2017-10 至 2020-01,英国南安普顿大学,数学学院,副研究员

  计算平台

  稀疏优化计算平台:SparseOpt-英文版、 SparseOpt-中文版

  双层规划计算平台:BiOpt

  论文/期刊

  部分第一作者文章 (* 通讯作者,全部发表文章可参考 Publications 或者 Google Scholar):

  Shenglong Zhou*, Ouya Wang*, Ziyan Luo, Yongxu Zhu, and Geoffrey Ye Li, Preconditioned inexact stochastic ADMM for deep models, Nature Machine Intelligence, 8, 234-245, 2026. RG, ArXiv, Code

  Shenglong Zhou*, Lili Pan, Naihua Xiu, and Geoffrey Ye Li, A 0/1 constrained optimization solving sample average approximation for chance constrained programming, Mathematics of Operations Research, 50, 4, 2688-2716, 2024. RG, ArXiv, Code

  Shenglong Zhou* and Geoffrey Ye Li, Federated learning via inexact ADMM, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45, 9699-9708, 2023. RG, ArXiv, Code

  Shenglong Zhou* and Geoffrey Ye Li, FedGiA: An efficient hybrid algorithm for federated learning, IEEE Transactions on Signal Processing, 71, 1493-1508, 2023. RG, ArXiv, Code

  Shenglong Zhou*, Sparse SVM for sufficient data reduction, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 5560-5571, 2022. RG, ArXiv, Code

  Shenglong Zhou*, Gradient projection newton pursuit for sparsity constrained optimization, Applied and Computational Harmonic Analysis, 61, 75-100, 2022. RG, ArXiv, Code

  Shenglong Zhou*, Ziyan Luo, Naihua Xiu, and Geoffrey Ye Li, Computing one-bit compressive sensing via double-sparsity constrained optimization, IEEE Transactions on Signal Processing, 70, 1593-1608, 2022. RG, ArXiv, Code

  Shenglong Zhou, Lili Pan, Naihua Xiu, and Houduo Qi, Quadratic convergence of smoothing Newton's method for 0/1 loss optimization, SIAM Journal on Optimization, 31, 3184-3211, 2021. RG, ArXiv, Code

  Shenglong Zhou, Lili Pan, Mu Li, and Meijuan Shang*, Newton hard-thresholding pursuit for sparse LCP via a new merit function, SIAM Journal on Scientific Computing, 43, A772-A799, 2021. RG, ArXiv, Code

  Shenglong Zhou, Naihua Xiu, and Houduo Qi, Global and quadratic convergence of Newton hard-thresholding pursuit, Journal of Machine Learning Research, 22, 1-45, 2021. RG, ArXiv, Code

  Shenglong Zhou, Lili Pan*, and Naihua Xiu, Newton method for L0-regularized optimization, Numerical Algorithms, 88, 1541-1570, 2021. RG, ArXiv, Code

  Shenglong Zhou, Naihua Xiu, and Houduo Qi*, Robust Euclidean embedding via EDM optimization, Mathematical Programming Computation, 12, 337-387, 2019. Code

  Shenglong Zhou, Naihua Xiu, and Houduo Qi*, A fast matrix majorization-projection method for penalized stress minimization with box constraints, IEEE Transactions on Signal Processing, 66, 4331-4346, 2018. Code

  Shenglong Zhou*, Naihua Xiu, Yingnan Wang, Lingchen Kong, and Houduo Qi, A Null-space-based weighted l1 minimization approach to compressed sensing, Information and Inference: A Journal of the IMA , 5, 76-102, 2016. RG, Code

  部分合作文章 ( * 通讯作者):

  Shuai Li, Shenglong Zhou*, and Ziyan Luo, Sparse quadratically constrained quadratic programming via semismooth Newton method, Mathematical Programming Computation, 2026. RG, ArXiv, Code

  Shan Sha, Shenglong Zhou*, Lingchen Kong, and Geoffrey Ye Li, Sparse decentralized federated learning, IEEE Transactions on Signal Processing, 73, 3406-3420, 2025. RG, ArXiv

  Ouya Wang, Shenglong Zhou*, and Geoffrey Ye Li, Frameworks on few-shot learning with applications in wireless communication, IEEE Transactions on Signal Processing, 73, 3857-3871, 2025. RG, ArXiv

  Jun Fan, Jie Sun, Ailin Yan, and Shenglong Zhou*, An oracle gradient regularized Newton method for quadratic measurements regression, Applied and Computational Harmonic Analysis, 78, 101775, 2025. RG, ArXiv

  Kaidi Xu, Shenglong Zhou*, and Geoffrey Ye Li, Federated reinforcement learning for resource allocation in V2X networks, IEEE Journal of Selected Topics in Signal Processing, 18, 1210-1221, 2024. RG, ArXiv

  Huajun Wang, Yuanhai Shao, Shenglong Zhou, Ce Zhang, and Naihua Xiu*, Support vector machine classifier via L0/1 soft-margin loss, IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 7253-7265, 2022. RG, ArXiv, Code

  部分最新Online文章 ( * 通讯作者):

  Shan Sha, Shenglong Zhou*, Xin Wang, Lingchen Kong, Geoffrey Ye Li, Decentralized federated learning by partial message exchange, 2026. RG, ArXiv

  Shenglong Zhou*, Shuai Li, Hui Zhang, and Ziyan Luo, Sharp-peak functions for exactly penalizing binary integer programming, 2025. RG, ArXiv

  Shuai Li and Shenglong Zhou*, Computing binary integer programming via a new exact penalty function, 2025. RG, ArXiv, Code

  Ouya Wang, Shenglong Zhou*, and Geoffrey Ye Li, BADM: Batch ADMM for deep learning, 2024. RG, ArXiv

  Shenglong Zhou*, Xianchao Xiu, and Dingtao Peng, Revisiting Lq (0≤q<1) norm regularized optimization, 2023. RG, ArXiv, Code

  科研项目

  2023-2028,主持,300万元,国家重点研发计划青年科学家项目,海量数据分析中的阶跃稀疏优化理论与方法

  2023-2026,主持,100万元,其他部市,机器学习中的0/1损失优化理论与二阶算法研究

  2023-2026,主持,100万元,自然科学类人才基金项目, 联邦学习中的最优化算法理论与应用

  获奖与荣誉

  2023年,IEEE MLSP 杰出论文奖

  2022年,国家高层次青年人才

  2019年,新世界数学奖博士论文优胜奖

  软件著作权

  部分软件与程序包(全部软件与程序可参考 Software 或者 Github)

  稀疏优化:参考稀疏优化计算平台 - SparseOpt

  阶跃优化:参考稀疏优化计算平台 - SparseOpt

  双层规划:参考双层规划计算平台 - BiOpt

  矩阵优化:SQREDM、PREEEDM

  联邦学习:FedADMM、FedGiA、FedEPM

  社会兼职

  2025 IEEE SPAWC 2025, Special Sessions Chairs

  2024 IEEE MLSP 2024, Publicity Chair

  2022 IEEE VTC2022-Fall, Workshop Chair

  以上就是小编为大家分享的:“北京交通大学硕士研究生导师信息:周声龙”,更多研究生导师信息,欢迎继续浏览新东方在线研究生导师频道。


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