王帅

教师简介

王帅，博士，副教授，博士生导师，中山大学“百人计划”引进人才，深圳市海外高层次人才
工作及学习经历简介如下：
2024年4月至今，中山大学，智能工程学院，副教授
2021年1月至2024年4月，中山大学，智能工程学院，助理教授
2015年9月至2020年7月，西安电子科技大学，人工智能学院，博士
2018年10月至2019年10月，英国萨里大学，计算机系，联合培养
2011年9月至2015年7月，西安电子科技大学，电子工程学院，学士

学科方向及课程教学

主要从事计算智能方法在复杂网络及人工智能及相关领域的研究和应用，包括：
1) 社会网络动力学研究以及数据挖掘；
2) 智能优化算法设计以及代理模型辅助的进化算法设计；
3) 图嵌入及其在网络相关分析、优化及集群控制问题上的应用；
4) 强化学习与深度学习方法的应用；
课题组立足于粤港澳大湾区，对于城市网络、医疗网络等复杂现实系统进行了分析和挖掘，完成了一些数据采集和整理工作，并尝试利用进化优化、强化学习、图学习等方法实现高效的知识挖掘和性能优化方法。

主讲课程：
本科生：《软件工程（含实验）》（课程负责人）、《人工智能编程语言》
研究生：《高等算法设计、分析与应用》

科研项目

1) 广东省自然科学基金面上项目，面向城市系统的风险感知和知识挖掘关键技术研究，2024-2026，主持；
2) 国家自然科学基金青年基金项目，考虑结构损毁的网络信息传播过程鲁棒性研究及智能优化方法设计，2023-2025，主持；
3) 深圳市基础研究专项重点项目，深海无人潜航器设计与运动控制方法研究，2022-2025，课题负责人；
4) 广东省基础与应用基础研究基金项目，复杂交通系统的网络化建模与智能优化算法研究，2021-2024，主持；
此外，主持教育教学改革项目、同创智慧医疗交叉学科人才培养基金、高校基本科研业务费、“百人计划”科研启动经费等项目5项；
参研国家自然科学基金面上项目、陕西省自然科学基础研究计划重点项目等研究。

代表性论著

近5年部分国际期刊文章：
[1] S. Wang and Y. Jin, “MFEA-RCIM: A multifactorial evolutionary algorithm for determining robust and influential seeds from competitive networks under structural failures,” IEEE Trans. on Cybernetics, vol. 55, no. 8. pp. 3624-3636, 2025. (中科院1区，Top，IF=10.5)
[2] S. Wang, Y. Ding, X. Ding, and X. Tan, “Solving the vehicle cooperation problem at signal-free intersection via an asynchronous deep reinforcement learning approach,” IEEE Internet of Things Journal, vol. 12, no. 13, pp. 23357-23372, 2025. (中科院2区，Top，IF=8.9)
[3] S. Cai, S. Wang (*), and M. Chen, “Finding robust and influential nodes from networks under cascading failures using a memetic algorithm,” Neurocomputing, vol. 589, p. 127704, 2024. (中科院2区，IF=6.5)
[4] Z, Ou and S. Wang (*), “Finding robust and influential nodes on directed networks using a memetic algorithm,” Swarm and Evolutionary Computation, vol. 87, p. 101542, 2024. (中科院2区，IF = 8.5)
[5] M. Chen, S. Wang (*), and J. Zhang, “A multi-factor evolutionary algorithm for solving the multi-tasking robust optimization problem on networked systems,” Applied Soft Computing, vol. 156, p. 111470, 2024. (中科院2区，Top，IF = 6.6)
[6] S. Wang, J. Zhang, and X. Tan, “PDLC-LIO: A precise and direct SLAM system toward large-scale environments with loop closures,” IEEE Trans. on Intelligent Transportation Systems, vol. 25, no. 1, pp. 626-637, 2024. (中科院2区，Top，IF = 8.4)
[7] S. Wang and W. Liu, “Enhancing the robustness of influential seeds towards structural failures on competitive networks via a memetic algorithm,” Knowledge-Based Systems, vol. 275, p. 110677, 2023. (中科院1区，Top，IF=7.6)
[8] S. Wang, B. Ding, and Y. Jin, “A multi-factorial evolutionary algorithm with asynchronous optimization processes for solving the robust influence maximization problem,” IEEE Computational Intelligence Magazine, vol. 18, no. 3, pp. 41-53, 2023. (中科院2区，IF=11.2)
[9] S. Wang and X. Tan, “Finding robust influential seeds from networked systems against structural failures using a niching memetic algorithm,” Applied Soft Computing, vol. 136, p. 110134, 2023. (中科院2区，Top，IF = 6.6)
[10] S. Wang, Y. Jin, and M. Cai, “Enhancing the robustness of networks against multiple damage models using a multifactorial evolutionary algorithm,” IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 53, no. 7, pp. 4176-4188, 2023. (中科院1区，Top，IF=8.7)
[11] S. Wang and X. Tan, “A Memetic algorithm for determining robust and influential seeds against structural perturbances in competitive networks,” Information Sciences, vol. 621, pp. 389-406, 2023. (中科院2区，IF=6.8)
[12] S. Wang and X. Tan, “Determining seeds with robust influential ability from multi-layer networks: A multi-factorial evolutionary approach,” Knowledge-Based Systems, vol. 246, p. 108697, 2022. (中科院1区，Top，IF=7.6)
[13] S. Wang and X. Tan, “Solving the robust influence maximization problem on multi-layer networks via a Memetic algorithm,” Applied Soft Computing, vol. 121, p. 108750, 2022. (中科院2区，Top，IF = 6.6)
[14] S. Wang, J. Liu, and Y. Jin, “A computationally efficient evolutionary algorithm for multiobjective network robustness optimization,” IEEE Trans. Evolutionary Computation, vol. 25, no. 3, pp. 419-432, 2021. (中科院1区，Top，IF=12)
[15] 王帅，刘静，一种针对网络结构破坏下的鲁棒影响力最大化问题的Memetic算法，计算机学报, 44(6), pp. 1153-1167, 2021. (计算机领域中文顶刊)
[16] S. Wang, J. Liu, and Y. Jin, “Finding influential nodes in multiplex networks using a memetic algorithm,” IEEE Trans. Cybernetics, vol. 51, no. 2, pp. 900-912, 2021. (中科院1区，Top，IF=10.5)
[17] S. Wang, J. Liu, and Y. Jin, “Surrogate-assisted robust optimization of large-scale networks based on graph embedding,” IEEE Trans. Evolutionary Computation, vol. 24, no. 4, pp. 735-749, 2020. (中科院1区，Top，IF=12)
[18] S. Wang, J. Liu, and Y. Jin, “Robust structural balance in signed networks using a multiobjective evolutionary algorithm,” IEEE Computational Intelligence Magazine, vol. 15, no. 2, pp. 24-35, 2020. (中科院2区，IF=11.2)

 

近5年国际会议文章：
[1] Z. Chen, J. Wu, S. Wang (*), and J. Huang, “A genetic deep reinforcement learning approach with prioritized experience replay strategy to solve the influence maximization problem on networks,” Applied Computational Intelligence, Informatics and Big Data2024, pp. 88-97, 2025.（依托科创课程指导本科生完成）
[2] J. Huang, S. Wang (*), C. Xia, Y. Yang, and W. Wang, “Solving the influence maximization problem via a deep-reinforcement-learning-guided evolutionary approach,” 2024 6th International Conferences on Data-driven Optimization of Complex Systems, pp. 150-155, 2024.（依托大创项目指导本科生完成）
[3] J. Tang, S. Wang (*), and C. Yang, “Constructing robust and influential networks against cascading failures via a multi-objective evolutionary algorithm,” ICSI 2024, Lecture Notes in Computer Science, vol 14788, pp. 277-288, 2024.
[4] M. Chen, S. Wang (*), “A genetic algorithm using diversity-concern principle to solve robust influence maximization problem on urban transportation networks,” Proceedings of the 2023 International Conference on Green Building, Civil Engineering and Smart City, vol. 328, pp 771-781, 2024.
[5] Y. He, S. Ren, S. Chen, and S. Wang (*), “Identifying key nodes in urban transportation systems using the information diffusion model,” Proceedings of the 2023 International Conference on Green Building, Civil Engineering and Smart City, vol. 328, pp 790-800, 2024. （依托科创课程指导本科生完成）
[6] S. Qumu, C. Zhu, Q. Luo, M. Zhou, and S. Wang (*), “Solving the influence maximization problem using a genetic deep reinforcement learning approach,” 2023 5-th International Conference on Data-driven-Optimization of Complex Systems, pp. 1-8, 2023. （依托科创课程指导本科生完成）
[7] M. Chen, S. Wang (*), and Z. Ou, “Solving the multi-tasking robust optimization on networks via structural reconstructions using a multi-factor evolutionary algorithm,” 2023 International Conference on Communication, Computing and Artificial Intelligence, pp. 35-41, 2023.
[8] Z. Ou, S. Wang (*), and S. Cai, “A Memetic algorithm for solving the robust influence problem on directed networks,” The Fourteenth International Conference on Swarm Intelligence, pp. 271-283, 2023.
[9] S. Cai, S. Wang (*), and Z. Ou, “A memetic algorithm to solve the robust influence maximization problems against cascading failures,” Genetic and Evolutionary Computation Conference Companion 2023, pp. 119-122, 2023. (CCF C类)
[10] M. Chen, S. Wang (*), and S. Cai, “Solving the multitasking robust influence maximization problem on networks using a multi-factorial evolutionary algorithm,” Genetic and Evolutionary Computation Conference Companion 2023, pp. 463-466, 2023. (CCF C类)
[11] J. Zhang, S. Wang (*), X. Tan, and M. Chen, “A comparative study of point cloud mapping algorithms towards heterogeneous traffic scenarios,” Proceedings of the 2022 International Conference on Green Building, Civil Engineering and Smart City, vol. 211, pp 1139–1150, 2023. (Best Paper Award)
 

（可参考：https://orcid.org/0000-0002-1796-7280）
 

荣誉获奖情况

部分个人获奖情况：
1) ICITE 2024会议优秀审稿人；
2) 中山大学第十二届教师教学竞赛课程教学赛道工科组优秀奖；
3) 2022年度中山大学优秀班主任；

 

指导竞赛及学生获奖：
1) GBCESC国际会议2022年最佳会议论文；
2) 第一届逸仙杯华南高校“智能+”创新大赛一等奖。

主要兼职

1) GECCO、CEC、DOCS、ICITE等国际会议审稿人；
2) IEEE Transactions on Evolutionary Computation、IEEE Transactions on Cybernetics、Swarm and Evolutionary Computation、IEEE Transactions on Network Science and Engineering、Information Sciences、Knowledge-based Systems、IEEE Systems Journal、Physica A等国际期刊审稿人；
3) 广东省科技咨询专家库候选专家、深圳市青年科技人才协会第九届理事会成员。

联系方式

电子邮箱：wangsh368@mail.sysu.edu.cn
 

身处鹏城扎根科技沃土，志在千里精研智能利器。
欢迎优秀的你加入团队！