Name: Wei-Neng Chen
School of Computer Science & Engineering
South China University of Technology
Guangzhou Higher Education Mega Centre
P. R. China
2016.3－now Professor School of Computer Science & Engineering, SCUT
2016.8 Newton Fund Visiting Scholar, University of Glasgow, UK
2014.01－2016.02 Associate Professor School of Advanced Computing, SYSU
2012.07－2013.12 Lecturer Department of Computer Science, SYSU
2006.09－2012.06 Ph.D. Department of Computer Science, SYSU
2002.09－2006.06 B.S Department of Computer Science, SYSU
Areas of Professional Interest
Computational Intelligence, Evolutionary Computation, Operations Research, Cloud Computing
Scientific Honors and Professional Services
Awardee of the National Natural Science Foundation of China (NSFC) Excellent Young Scholars Program in 2016
Awardee of the Natural Science Foundation of Guangdong Province Outstanding Young Scholars Program in 2015
Awardee of the Guangzhou Pearl River New Star of Science and Technology in 2015
Recipient of the Guangdong Special Support Program for Young Innovative Talents in 2015
Vice Chair, IEEE Guangzhou Subsection
Member, CCF Artificial Intelligence and Pattern Recognition Specialized Committee
Member, CCF / IEEE / ACM
Selected Journal Papers
(1)Qiang Yang, Wei-neng Chen (Corresponding Author), et al., “Adaptive Multimodal Continuous Ant Colony Optimization,”IEEE Transactions on Evolutionary Computation, vol. 21, no. 2, pp. 191-205, 2017
(2)Qiang Yang, Wei-neng Chen (Corresponding Author), et al., “Multimodal Estimation of Distribution Algorithms,”IEEE Transactions on Cybernetics, vol. 47, no. 3, pp. 636-650, 2017.
(3)Ni Chen, Wei-neng Chen (Corresponding Author), Yue-jiao Gong, Zhi-hui Zhan, Jun Zhang, Yun Li and Yu-song Tan, “An Evolutionary Algorithm with Double-Level Archives for Multi-Objective Optimization,”IEEE Transactions on Cybernetics, vol. 45, no. 9, pp. 1851-1863, 2015.
(4)Wei-neng Chen, Jun Zhang, Ying Lin, Ni Chen, Zhi-hui Zhan, H.S.H. Chung, Yun Li and Yu-hui Shi, “Particle Swarm Optimization with an Aging Leader and Challengers”, IEEE Transactions on Evolutionary Computation, vol. 17, no. 2, pp. 241-258, 2013. [ESI Highly Cited Paper]
(5)Wei-neng Chen and Jun Zhang, “Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler”, IEEE Transactions on Software Engineering, vol. 39, no. 1, pp. 1-17, 2013.
(6)M. Shen, Wei-neng Chen (Corresponding Author), et. al, “Optimal Selection of Parameters for Non-uniform Embedding of Chaotic Time Series Using Ant Colony Optimization”, IEEE Transactions on Cybernetics, vol.43, no.2, pp. 790 - 802, 2013.
(7)Wei-neng Chen, Jun Zhang, H.S.H. Chung, Wen-Liang Zhong, Wei-Gang Wu and Yu-hui Shi, “A novel set-based particle swarm optimization method for discrete optimization problem,” IEEE Transactions on Evolutionary Computation, vol. 14, no. 2, pp. 278-300, 2010.
(8)Wei-neng Chen, Jun Zhang, H.S.H. Chung, Rui-Zhang Huang and Ou Liu, “Optimizing Discounted Cash Flows in Project Scheduling - An Ant Colony Optimization Approach,” IEEE Transactions on System, Man, and Cybernetics, Part C, vol. 40, no. 1, pp. 64-77, 2010.
(9)Wei-neng Chen and Jun Zhang, “An ant colony optimization approach to a Grid workflow scheduling problem with various QoS requirements”, IEEE Transactions on System, Man, and Cybernetics, Part C, vol. 39, no. 1, pp. 29-43, 2009.
(10)Qiang Yang, Wei-neng Chen (Corresponding Author), et al. ,“Segment-Based Predominant Learning Swarm Optimizer for Large-Scale Optimization,” IEEE Transactions on Cybernetics, in press
(11)Xuyun Wen, Wei-neng Chen (Corresponding Author), et al. “A Maximal Clique Based Multiobjective Evolutionary Algorithm for Overlapping Community Detection,”IEEE Transactions on Evolutionary Computation, in press
(12)Qunfeng Liu, Wei-neng Chen (Corresponding Author), et al. ,“Benchmarking Stochastic Algorithms for Global Optimization Problems by Visualizing Confidence Intervals,”IEEE Transactions on Cybernetics, in press
(13)Ya-hui Jia, Wei-neng Chen (Corresponding Author), et al. , “A Dynamic Logistic Dispatching System With Set-Based Particle Swarm Optimization,”IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press
(1)Swarm Intelligence Algorithms & Applications, NSFC Excellent Young Scholars Program, PI，2017.1-2019.12
(2)Large-scale Swarm Intelligence Algorithms, Natural Science Foundation of Guangdong Province Outstanding Young Scholars Program, PI，2015.8-2019.8
(3)Research into Dynamic Distributed Particle Swarm Optimization Algorithms, NSFC-RS (Royal Society, UK) Newton Fund Program, 2015.3-2017.3
(4)Cloud Resource Allocation and Task Scheduling with Swarm Intelligence, Guangzhou Pearl River New Star of Science and Technology Program, 2015.4-2018.3
(5)Dynamic Distributed Particle Swarm Optimization for Multi-Workflow Scheduling in Cloud Computing, NSFC, 2014.1-2017.12
(1)IEEE Computational Intelligence Society (IEEE CIS) Ph.D. Outstanding Dissertation Award, 2016
(2)CCF Excellent Ph.D. Dissertation Award, 2012
During lithiation and detlithiation, substantial volumetric changes occur within the electrode materials used for rechargeable lithium batteries. The magnitude of these deformations is inherently linked to the electrical capacity of the battery electrical capacity, which tends to degrade with repeated cycling. In this dissertation, the relationship between electrical discharge capacity and mechanical deformation state is examined using in-situ imaging of the working electrode surface within a custom CR2032 coin cell lithium battery. Digital image correlation is used to quantify electrode strains throughout the discharge-charge process. The effect of constraint due to substrate stiffness is investigated for two film materials: traditional graphite and a carbon nanotube based composite. Results for all cases show that as discharge capacity decreases with repeated cycling, increasing residual electrode strains are observed. The thin, compliant foil substrates allowed over double the bi-axial strain state to be induced within electrodes, compared to that found for the thick copper disk substrates under the same electrical cycling conditions. While this work shows that substrates play a significant role in strain development, additional tests are done to investigate the effects of adhesion quality between electrode films and substrates on electrochemical performance of lithium batteries. These effects are probed using a laser spallation technique to quantify the adhesion strength between film and substrate layer. The benefits of surface treatment designed to improve adhesion are also investigated. At last, delamination test of graphite electrode film “sandwiched” by copper substrate are performed. And the results show that surface treatment by mechanical or chemical manner can improve the adhesion dramatically.
Chen, Jubin, "Mechanics of electrode materials in lithium battery applications." (2015). Electronic Theses and Dissertations. Paper 2223.