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复旦大学信息科学与工程学院导师教师师资介绍简介-丁洁

本站小编 Free考研考试/2021-01-10

丁洁
电子工程系
职称:青年副研究员
职务:
电子邮件:dingjie@fudan.edu.cn
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2019.09-至今: 复旦大学信息科学与工程学院,青年副研究员
2018.07-2019.08:新加坡资讯通信研究院,研究员I级
2013.08-2018.06: 新加坡南洋理工大学,博士

2008.09-2012.06: 哈尔滨工程大学,本科






J. Ding, C. Wen , G. Li et al. “Target Controllability in Multilayer Networks viaMinimum-Cost Maximum-Flow Method",IEEE Trans. on Neural Networks and Learning Systems,DOI: 10.1109/TNNLS.2020.**, 2020.
J. Ding, C. Wen, G. Li, X. Yang and T. Hu, “Sparsity-inspired optimal topology control ofcomplex networks",IEEE Trans. on Network Science and Engineering,DOI:10.1109/TNSE.2019.**,2019.

J. Ding, C. Wen, G. Li and Z. Chen, “Key node selection in controlling complex networksvia convex optimization”, IEEE Trans. on Cybernetics, DOI:10.1109/TCYB.2018.**, 2019.
G. Li*, J. Ding*, C. Wen and J. Huang, “Minimum cost control of directed networkswith selectable control inputs”, IEEE Trans. on Cybernetics, 49(12),4431- 4440, 2019. (*contributed equally)
G. Li*, J. Ding*, C. Wen, L. Wang and F. Guo, “Controlling directed networks withevolving topologies”, IEEE Trans. on Control of Network Systems, 6(1),176- 190, 2018. (*contributed equally)
J. Ding, C. Wen and G. Li, “Key node selection in minimum cost control of complexnetworks”, Physica A: Statistical Mechanics and its Applications, 486, 251-261, 2017.
J. Ding, C. Wen and G. Li, “Optimal control of weighted networks based on nodeconnection strength”, The 27th IEEE International Symposium on Industrial Electronics,2017.
J. Ding, C. Wen, G. Li and C. Chua, “Locality sensitive batch feature extraction forhigh-dimensional Data”, Neurocomputing, 171, 664-672, 2016.

G. Li, J. Ding, C. Wen and J. Pei, “Optimal control of complex networks based onmatrix differentiation”, Europhysics Letters, 115(6), 68005, 2016.
G. Li, C. Wen, W. Wei, Y. Xu, J. Ding, G. Zhao and L. Shi, “Trace ratio criterionfor feature extraction in classification”, Mathematical Problems in Engineering, 2014,
J. Ding, G. Li, C. Wen and C. Chua, “Min-max discriminant analysis based ongradient method for feature extraction”, 13th International Conference on Control,Automation, Robotics and Vision (ICARCV), Singapore,2014,725204, 2014.









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