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Jinghui Zhong
Associate Professor
School of Computer Science and Engineering
South China  University of Technology, Guangzhou, China
    
Email: jinghuizhong at gmail dot com

I am currently an Associate Professor with the School of Computer Science and Engineering, South China University of Technology, China. I received the Ph.D. degrees from the School of Information Science and Technology, Sun YAT-SEN University in  2012. From 2013 to 2016, I worked as a Research Fellow in the School of Computer Science and Engineering, Nanyang Technological University, Singapore.


NEWs

Call for papers: We are organizing a workshop "Evolutionary computation and its applications" hosted at UIC 2018 in Guangzhou, China. You are welcome to submit your work and come to enjoy  the conference! Submission deadline is: July 5, 2018.  



RESEARCH INTERESTS
  • Computational Intelligence: Genetic Programming,  Differential Evolution, Multi-tasking Evolutionary Algorithm, and others.
  • Machine Learning: Gaussian Process, EM algorithm, Deep Learning, and others
  • Agent-Based Modeling and Simulation.

SELECTED PUBLICATIONS

  1. J. Zhong, L. Feng, and Y.-S. Ong, "Gene Expression Programming: A Survey," IEEE Computational Intelligence Magazine, 2017 [pdf].
  2. J. Zhong, W. Cai, M. Lees, and L. Luo, "Automatic Model Construction for the Behaviour of Human Crowds", Applied Soft Computing, 2017 (accepted) [source code and dataset] [pdf]
  3. J. Zhong, W. Cai, L. Luo, and M. Zhao, "Learning behavior patterns from video for agent-based crowd modeling and simulation," Autonomous Agents and Multi-Agent Systems,2016, 30(5): 990-1019.  [source code and dataset]  [pdf]
  4. J. Zhong, Y.-S. Ong, and W. Cai, “Self-Learning Gene Expression Programming,” IEEE Transactions on Evolutionary Computation, 2016, 20(1): 65-80. [source code and dataset]
  5. J. Zhong, N. Hu, W. Cai, M. Lees, and L.B. Luo, Density-Based Evolutionary Framework for Crowd Model Calibration, ” Journal of Computational Science, 6 (2015): 11-22.
  6. J. Zhong, M. Shen, J. Zhang, H.S.H. Chung, Y.H. Shi, Y. Li, “A Differential Evolution Algorithm with Dual Populations for Solving Periodic Railway Timetable Scheduling Problem IEEE Transactions on Evolutionary Computation, Vol. 17, No. 4, pp.512-527, August 2013.
  7. Y. Xue, J. Zhong*, and et al., “IBED: Combining IBEA and DE for Optimal Feature Selection in Software Product Line Engineering,” Applied Soft Computing, Vol.49, pp.1215-1231, 2016.
  8. L. Luo, H. Yin, W. Cai, J. Zhong, M. Lees, “Design and Evaluation of a Data-driven Scenario Generation Framework for Game-based Training,” IEEE Transactions on Computational Intelligence and AI in Gamesvol. 9, no. 3, pp. 213-226, Sept. 2017.
  9. M. Zhao, J. Zhong, and W. Cai, “A Role-dependent Data-driven Approach for High Density Crowd Behavior Modeling,” ACM Transactions on Modeling and Computer Simulation, 2017 (Accepted). 
  10. J. Zhong, L. Luo, W. Cai, and M. Lees, “Automatic Rule Identification for Agent-Based Crowd Models Through Gene Expression Programming,” In Proceedings of the 2014 International Conference on Autonomous Agents and Multi-agent Systems (AAMAS 2014), pp.1125-1132, International Foundation for Autonomous Agents and Multiagent Systems, 2014.


Professional Activities


PC member of the following conferences:

     ICCS2018, ICDIS2018CST2017ICONIP2017ICCS2017ICCS2016ICONIP 2016WCSN2016ICCS2015CCDM2011

Reviewer of the following Journals:
  • IEEE Transactions on Evolutionary Computation
  • IEEE Transactions on Cybernetics
  • IEEE Computational Intelligence Magazine  
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Network and Service Management 
  • ACM Transactions on Modeling and Computer Simulation
  • IEEE Access
  • Journal of Applied Soft Computing
  • Journal of Computational Science
  • Future Generation Computer Systems
  • Networks and Spatial Economics
  • Neural Computing and Applications
  • Neural Processing Letters
  • Engineering Optimization
Honors and Awards

Grants
  • Distributed Genetic Programming and Its Applications, Fundamental Research Funds for the Central Universities, 2017/012018/12, PI
  • A Cooperative Coevolutionary Genetic Programming Framework for Crowd Modeling and Simulation, National Natural Science Foundation of China, 2017/012019/12, PI