王振坤，IEEE高级会员、南方科技大学助理教授、广东省全驱系统理论与技术重点实验室副主任、博士生导师，研究方向为人工智能与调度优化，以第一/通讯作者身份在IEEE汇刊、ICML、NeurIPS等国际高水平期刊和会议上发表论文80余篇（其中IEEE汇刊论文20篇和CCF A类会议论文12篇），获2023年度中国仿真学会自然科学奖二等奖（1/7）、2023年度广东省自然科学二等奖（2/5）、第八届全国青年人工智能创新创业大会创新组一等奖（1/3）、第六届智能优化与调度学术会议青年科学家奖、 华为公司火花奖、深圳市“海外高层次人才”等荣誉；主持国自然面上和青年项目、省市级项目多项，担任两个JCR Q1期刊的副编辑（Associate Editor）、IEEE计算智能学会深圳分会学生事务主席、中国人工智能学会青年工作委员会委员、中国仿真学会智能仿真优化与调度专委会委员以及多个国际会议的程序委员会委员。

研究方向

多目标优化与启发式算法

神经组合优化与供应链管理

数据驱动的复杂优化

医学影像处理

工作经历

2020 年 6 月 - 至今  南方科技大学，系统设计与智能制造学院，助理教授

2020 年 4 月 - 5 月  香港城市大学深圳研究院，研究员

2019 年 1 月 - 2020 年 3 月  香港城市大学，电脑科学系，博士后研究员

2017 年 2 月 - 2019 年 1 月  南洋理工大学，计算机科学与工程学院，博士后研究员

教育经历

2011 年 - 2016 年  西安电子科技大学，电子工程学院，博士

2007 年 - 2011 年  山东建筑大学，信息与电气工程学院，学士

发表文章

Journal publications

[1] Weifeng Gao, Genghui Li, Qingfu Zhang, Yuting Luo and Zhenkun Wang. “Solving Nonlinear Equation Systems by a Two-Phase Evolutionary Algorithm”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press.(TSMC, IF: 7.351)

[2] Jianping Luo, Xiongwen Huang, Yun Yang, Xia Li, Zhenkun Wang, Jiqiang Feng. “A Many-objective Particle Swarm Optimizer based on Indicator and Direction Vectors for Many-objective Optimization”. Information Sciences, 514: 166-202 2020.(INS, IF: 5.524)

[3] Chen Xu, Yiyuan Chai, Sitian Qin, Zhenkun Wang, Jiqiang Feng. “A Neurodynamic Approach to Nonsmooth Pseudoconvex Optimization Problems” , Neural Networks, 124: 180-192.(NN, IF: 7.197)

[4] Hao Li, Yew-Soon Ong, Maoguo Gong and Zhenkun Wang. “Evolutionary Multitasking Sparse Reconstruction: Framework and Case Study”, IEEE Transactions on Evolutionary Computation, 23(5): 733-747, 2019.(TEVC, IF: 8.508)

[5] Jianping Luo, Abhishek Gupta, Yew-Soon Ong and Zhenkun Wang. “Evolutionary Optimization of Expensive Multi-objective Problems with Gaussian Co-subPF Surrogates”, IEEE Transactions on Cybernetics, 49(5): 1708-1721, 2019.(TCYB, IF: 10.387)

[6] Zhenkun Wang, Yew-Soon Ong, Jianyong Sun, Abhishek Gupta and Qingfu Zhang. “A Generator for Multiobjective Test Problems with Difficult-to-Approximate Pareto Front Boundaries” IEEE Transactions on Evolutionary Computation, 23(4): 556-571, 2019.(TEVC, IF: 8.508)

[7] Zhenkun Wang, Yew-Soon Ong and Hisao Ishibuchi. “On Scalable Multiobjective Test Problems with Hardly-dominated Boundaries”, IEEE Transactions on Evolutionary Computation, 23(2): 217-231, 2019.(TEVC, IF: 8.508)  

[8] Zhenkun Wang, Qingfu Zhang, Hui Li, Hisao Ishibuchi and Licheng Jiao. “On The Use of Two Reference Points in Decomposition Based Multiobjective Evolutionary Algorithms,”, Swarm and Evolutionary Computation, 34: 89-102, 2017.(Swarm & EC, IF: 6.33)

[9] Maoguo Gong, Yue Wu, Qing Cai, Wenping Ma, Kai Qin, Zhenkun Wang and Licheng Jiao. “Discrete Particle Swarm Optimization for High-order Graph Matching”, Information Sciences, 328: 158-171 2016.(INS, IF: 5.524)

[10] Zhenkun Wang, Qingfu Zhang, Aimin Zhou, Maoguo Gong and Licheng Jiao. Adaptive Replacement Strategies for MOEA/D, IEEE Transactions on Cybernetics, 46(2): 474-486, 2016.(TCYB, IF: 10.387) [ESI highly cited paper]

Conference publications

[1] Qingyu Tan, Zhenkun Wang, Yew-Soon Ong, Kin Huat Low. “Evolutionary Optimization-based Mission Planning for UAS Traffic Management (UTM)”, 2019 International Conference on Unmanned Aircraft Systems, p. 952-958, (ICUAS) 2019.
[2] Mohamed Faisal B Mohamed Salleh, Wanchao Chi, Zhenkun Wang, Shuangyao Huang, Da-Yang Tan, Tingting Huang, Kin Huat Low. “Preliminary Concept of Adaptive Urban Airspace Management for Unmanned Aircraft Operations” AIAA Information Systems-AIAA Infotech@ Aerospace p. 2260, (AIAA) 2018.
[3] Xingxing Hao, Jing Liu, Zhenkun Wang. “An Improved Global Replacement Strategy for MOEA/D on Many-objective Kanpsack Problems.” 2017 IEEE Congress on Automation Science and Engineering, p. 624-629, (CASE) 2017.
[4] Improved Adaptive Global Replacement Scheme for MOEA/D-AGR.
Hiu-Hin Tam, Man-Fai Leung, Zhenkun Wang, Sin-Chun Ng, Chi-Chung Cheung, Andrew K Lui.
In 2016 IEEE Congress on Evolutionary Computation, p. 2153-2160, (CEC) 2016.
[5] Zhenkun Wang, Qingfu Zhang, Hui Li. “Balancing Convergence and Diversity by Using Two Different Reproduction Operators in MOEA/D: Some Preliminary Work.” 2015 IEEE Conference on Systems, Mans and Cybernetics, p. 2849–2854. (SMC) 2015.
[6] Zhenkun Wang, Qingfu Zhang, Maoguo Gong, Aimin Zhou. “A Replacement Strategy for Balancing Convergence and Diversity in MOEA/D.” 2014 IEEE Congress on Evolutionary Computation, p. 2132-2139, (CEC) 2014.