深圳大学计算机与软件学院
College of Computer Science and Software Engineering, SZU
林秋镇

网络与信息安全研究所副所长 副教授

网络与信息安全研究所

Email:qiuzhlin@szu.edu.cn

林秋镇

      林秋镇,中共党员,2014年博士毕业于香港城市大学,深圳大学计算机与软件学院研究员、副教授,博导,网络与信息安全研究所副所长,长期聚焦研究基于进化计算的多目标优化理论与算法,结合机器学习、概率统计、模糊估计、多智能体、协作学习等方法,应用进化学习原理与机制获取多目标问题的求解特征与估计帕累托最优前沿(Pareto-optimal Front),提出了高效降维、资源分配、高效搜索、集成框架等一般多目标优化理论方法,结合个体学习、群体学习、竞争与协同学习等进化机制改进了多种进化算法用于求解各类具有高维、多模、昂贵、大规模、非规则等复杂特征的多目标优化问题,缓解了多目标优化中的收敛性与多样性平衡难题。这些基于进化计算的多目标优化理论与算法可以广泛应用于各种人工智能系统,满足其多个冲突目标的优化需求,增强人工智能技术在实际工程的应用效果,属于工程技术优化的基础理论算法,具有重要的科学意义和应用价值。

 

研究领域:进化计算,多目标优化,深度学习,机器学习; 

 

主要学术成果与学术任职:

(1)2022年7月止累计共发表SCI论文102篇,其中IEEE汇刊论文37篇,大多数论文发表在智能计算领域的顶级期刊,如IEEE Transactions on Evolutionary Computation (2021年影响因子:16.497), IEEE Transactions on Cybernetics (2021年影响因子:19.118), IEEE Transactions on Systems, Man, and Cybernetics: Systems (2021年影响因子:11.471), IEEE Transactions on Neural Networks and Learning Systems (2021年影响因子:10.47),  IEEE Transactions on Emerging Topics in Computational Intelligence (2021年影响因子:4.34) 等等

(2)2021年开始,担任智能计算顶级期刊IEEE Transactions on Evolutionary Computation(2021年影响因子:16.497)的副编辑(Associate Editor);2014年开始,担任TEVC、TCYB、TMSC、TNNLS、TVT、TITS、TETCI等IEEE汇刊的审稿专家;负责组织ICIC 2020的Special Session 8会议,担任ICICIP 2021、ICIST 2021、ICACI2021、EMO 2021、ACAIT 2020、SEAL 2017等国际会议的程序委员会委员;

(3)所提出的多目标优化算法分别应用于智能系统的入侵检测功能和路径规划,分别获得了中国自动化学会科技进步奖励一等奖(排名第三)、吴文俊人工智能科技进步奖一等奖(排名第六)和广东省科技进步奖二等奖(排名第七),两项深圳市自然科学奖励二等奖(排名第三、排名第六)和中国人工智能学会2019年度最佳青年科技成果奖(独立完成);

(4)在科研成果应用方面,申请人将所提出的多目标优化算法分别用于入侵检测、作业调度、路径规划、推荐方法、图像重构,获得国家发明专利授权6项和软件著作权2项,所提出的多目标优化算法参加华为在ICAPS 2021(The International Conference on Automated Planning and Scheduling 2021)举行的实际场景下动态取货和配送比赛,最终在153个团队比赛中取得了第一名金奖,参加2019年IEEE国际进化计算大会(IEEE CEC 2019,进化计算领域顶会)举行的多模态多目标优化竞赛并取得了亚军的成绩。

(5)2014年、2018年分别获得国家自然科学基金青年项目与面上项目资助各一项;2017年获得广东省自然科学基金面上项目一项;2018年和2020年分别获得深圳市科创委面上项目各一项,累计科研项目经费超过400万。

(6)荣获深圳市孔雀计划C类人才,深圳市高层次人才后备级,深圳大学荔园优青。

   全部论文列表可见: https://dblp.org/pid/22/8016.html

   Google学术引用见:https://scholar.google.com/citations?user=LgBI8LMAAAAJ&hl=en.

 

   本人作为(共同)通讯作者指导研究生以第一作者发表论文20余篇,10余名研究生在本人指导下已成功申请南洋理工大学、香港城市大学、香港理工大学、深圳大学等国内外知名高校博士学位并继续深造。欢迎有兴趣去国外深造读博的同学加入科研小组。研究组里的大多数研究生成果丰富,目前研究小组里有在读博士5名,硕士生10名,多名在读研究生荣获研究生国家奖学金和优秀毕业研究生称号,就业情况良好,多名毕业生进入腾讯、华为、中兴、京东、小米、迅雷、深交所等公司工作。

 

   科研团队每年拟招收3-5名研究生,1名博士生,长期招聘博士后,欢迎感兴趣的同学或博士联系邮箱: qiuzhlin@szu.edu.cn.

 

代表性论文:

[1] S.B. Liu (博士生), Q.Z. Lin (通讯作者), K.C. Wong, C.A. Coello Coello, J.Q. Li, Z. Ming, J. Zhang, A Self-Guided Reference Vector Strategy for Many-objective Evolutionary Algorithms, IEEE Transactions on Cybernetics, 2022, 52(2): 1164-1178. 

https://ieeexplore.ieee.org/document/9090337

[2] Q.Z. Lin, G.M. Jin, Y.P. Ma, K.C. Wong, C.A. Coello Coello, J.Q. Li, J.Y. Chen, J. Zhang, A Diversity-Enhanced Resource Allocation Strategy for Decomposition-Based Multiobjective Evolutionary Algorithm, IEEE Transactions on Cybernetics, 2018, 48(8): 2388-2401.

https://ieeexplore.ieee.org/document/8026151

[3] Q.L. Zhu (研究生), Q.Z. Lin (通讯作者), J.Q. Li, C.A. Coello Coello, Z. Ming (通讯作者), J.Y. Chen, J. Zhang, An Elite Gene Guided Reproduction Operator for Many-Objective Optimization, IEEE Transactions on Cybernetics, 2021, 51(2): 765-778.

https://ieeexplore.ieee.org/document/8820137

[4] W.J. Wang (博后), S.Q Yang (研究生), Q.Z. Lin (通讯作者), Q.F. Zhang, K.C. Wong, C.A. Coello Coello, J.Y. Chen, An Effective Ensemble Framework for Multiobjective Optimization, IEEE Transactions on Evolutionary Computation, 2019, 23(4): 645-659.    

https://ieeexplore.ieee.org/document/8519635

[5] Q.Z. Lin, S.B. Liu, K.C. Wong, M.G. Gong, C.A. Coello Coello, J.Y. Chen, J. Zhang, A Clustering-Based Evolutionary Algorithm for Many-Objective Optimization Problems, IEEE Transactions on Evolutionary Computation, 2019, 23(3): 391-405.

https://ieeexplore.ieee.org/document/8444681

[6] Q.Z. Lin, S.B. Liu, Q.L. Zhu, C.Y. Tang, R.Z. Song, J.Y. Chen, C.A. Coello Coello, K.C. Wong, J. Zhang, Particle Swarm Optimization With a Balanceable Fitness Estimation for Many-Objective Optimization Problems, IEEE Transactions on Evolutionary Computation, 2018, 22(1): 32-46.

https://ieeexplore.ieee.org/document/7782848

[7] Q.Z. Lin, W. Lin, Z.X. Zhu, M.G. Gong, J.Q. Li, C.A. Coello Coello, Multimodal Multiobjective Evolutionary Optimization with Dual Clustering in Decision and Objective Spaces, IEEE Transactions on Evolutionary Computation, 2021, 25(1): 130-144.  

https://ieeexplore.ieee.org/document/9139318

[8] Q.Z. Lin, X.F. Wu, L.J. Ma, J.Q. Li, M.G. Gong, C.A. Coello Coello, An Ensemble Surrogate-based Framework for Expensive Multiobjective Evolutionary Optimization, IEEE Transactions on Evolutionary Computation, 2021, in press: 1-15.

https://ieeexplore.ieee.org/document/9509584

[9] S.B. Liu (博士生), Q.Z. Lin (通讯作者), K.C. Wong, Q. Li, K.C. Tan (通讯作者), Evolutionary Large-Scale Multiobjective Optimization: Benchmarks and Algorithms, IEEE Transactions on Evolutionary Computation, 2021, in press: 1-14.

https://ieeexplore.ieee.org/document/9494411

[10] S.B. Liu (博士生), Q.Z. Lin (通讯作者), Q. Li, K.C. Tan (通讯作者), A Comprehensive Competitive Swarm Optimizer for Large-Scale Multiobjective Optimization, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, in press: 1-14.

https://ieeexplore.ieee.org/document/9647011

[11] J.Q. Li, T. Sun, Q.Z. Lin (通讯作者), M. Jiang, K.C. Tan, Reducing Negative Transfer Learning via Clustering for Dynamic Multiobjective Optimization, IEEE Transactions on Evolutionary Computation, 2022, in press: 1-15.

https://ieeexplore.ieee.org/document/9684563 

[12]  J.K. Ji, Y.J. Tang, L.J. Ma, J.Q. Li, Q.Z. Lin (通讯作者), Z. Tang, Y.K. Todo (通讯作者), Accuracy Versus Simplification in an Approximate Logic Neural Model, IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(11): 5194-5207.

https://ieeexplore.ieee.org/document/9250635

[13] Q.Z. Lin, Z.X. Fang, Y. Chen, K.C. Tan, Y. Li, Evolutionary Architectural Search for Generative Adversarial Networks, IEEE Transactions on Emerging Topics in Computational Intelligence, 2022, in press: 1-12.

https://ieeexplore.ieee.org/document/9686068

[14] J.W. Liang (研究生), Q.Z. Lin (通讯作者), J.Y. Chen, Y.Y. Zhu, A Filter Model Based on Hidden Generalized Mixture Transition Distribution Model for Intrusion Detection System in Vehicle Ad Hoc Networks, IEEE Transactions on Intelligent Transportation Systems, 2020, 21(7): 2707-2722.

https://ieeexplore.ieee.org/document/8734149

[15] Y. He, Y. Wang, Q.Z. Lin (通讯作者), J.Q. Li, Meta-Hierarchical Reinforcement Learning (MHRL)-based Dynamic Resource Allocation for Dynamic Vehicular Networks, IEEE Transactions on Vehicular Technology, 2022, 71(4): 3495 - 3506.  

https://ieeexplore.ieee.org/document/9695369/

[16] J.K. Ji, M.H. Dong, Q.Z. Lin (通讯作者), K. C. Tan, Noninvasive Cuffless Blood Pressure Estimation With Dendritic Neural Regression, IEEE Transactions on Cybernetics, 2022, in press: 1-13

https://ieeexplore.ieee.org/document/9703247

[17] L.J. Ma, Z.Y. Shao, X.C. Li, Q.Z. Lin (通讯作者), J.Q. Li, Victor C. M. Leung, Asoke K. Nandi, Influence Maximization in Complex Networks by Using Evolutionary Deep Reinforcement Learning, IEEE Transactions on Emerging Topics in Computational Intelligence, 2022, in press: 1-15. 

https://ieeexplore.ieee.org/document/9679820

[18] S.B. Liu, Q.Z. Lin (通讯作者), Q. Li, K. C. Tan (通讯作者), A Comprehensive Competitive Swarm Optimizer for Large-Scale Multiobjective Optimization, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, in press: 1-14. 

https://ieeexplore.ieee.org/document/9647011

[19] S.B. Liu, Q.Z. Lin (通讯作者), Y. Tian, K. C. Tan (通讯作者), A Variable Importance-Based Differential Evolution for Large-Scale Multiobjective Optimization, IEEE Transactions on Cybernetics, 2022, in press: 1-15. 

https://ieeexplore.ieee.org/document/9517038

[20] J.K. Ji, M.H. Dong, Q.Z. Lin (通讯作者), K. C. Tan, Forecasting Wind Speed Time Series Via Dendritic Neural Regression, IEEE Computational Intelligence Magazine, 2021, 16(3): 50-66. 

https://ieeexplore.ieee.org/document/9492146

[21] F. Chen, D. Wang, Q.Z. Lin (通讯作者), J.Y. Chen, Z. Ming, W. Yu, J. Qin, Towards Dynamic Verifiable Pattern Matching, IEEE Transactions on Big Data, 2021, 7 (2) : 421-435. 

https://ieeexplore.ieee.org/document/8454827/

个人主页:https://dblp.org/pid/22/8016.html