Changwu HUANG

2019-11-06

Changwu Huang obtained his bachelor degree from Southwest Jiaotong University in 2010, master degree from Beijing Jiaotong University in 2013, and doctor degree from Institut National des Sciences Appliquées de Rouen Normandie (INSA Rouen Normandie), France, in 2018. Currently, Dr. Huang is a postdoctoral researcher in Prof. Xin Yao’s team, Department of Computer Science and Engineering, Southern University of Science and Technology. His research interests cover different aspects of computational intelligence, including optimization, evolutionary algorithms, machine learning, surrogate-assisted evolutionary algorithms, algorithm portfolio, automatic algorithm configuration (automatic parameter tuning) and their applications.

Journal Papers

  • Huang, Y. Li, and X. Yao, “A Survey of Automatic Parameter Tuning Methods for Metaheuristics,” IEEE Transactions on Evolutionary Computation (Early Access), 2019.
  • Huang, B. Yuan, Y. Li, and X. Yao, “Automatic Parameter Tuning using Bayesian Optimization Method,” 2019 IEEE Congress on Evolutionary Computation (CEC), Jun. 2019.
  • Tong, C. Huang, J. Liu, and X. Yao, “Voronoi-based Efficient Surrogate-assisted Evolutionary Algorithm for Very Expensive Problems,” 2019 IEEE Congress on Evolutionary Computation (CEC), Jun. 2019.
  • Huang, B. Radi, A. El Hami, and H. Bai, “CMA evolution strategy assisted by kriging model and approximate ranking,” Applied Intelligence, vol. 48, no. 11, pp. 4288–4304, Jun. 2018.
  • Huang, A. El Hami, and B. Radi, “Metamodel-based inverse method for parameter identification: elastic–plastic damage model,” Engineering Optimization, vol. 49, no. 4, pp. 633–653, Jul. 2016.
  • Huang, B. Radi, and A. E. Hami, “Uncertainty analysis of deep drawing using surrogate model based probabilistic method,” The International Journal of Advanced Manufacturing Technology, vol. 86, no. 9–12, pp. 3229–3240, Feb. 2016.
  • Huang, G. Yang, N. Fu, and J. Xie, “Research on Fretting Fatigue Life of Interference Fit and its Influencing Factors,” Applied Mechanics and Materials, vol. 251, pp. 293–300, Dec. 2012.

Research

黄长武博士自2018年加入姚新教授团队做博士后以来,已在国际刊物及会议上发表科研论文 4篇(其中3篇为第一作者),其中一篇发表于演化计算领域顶级期刊IEEE Transactions on Evolutionary Computation,另有2篇会议论文被接收(SSCI 2019)。通过研究自动化、智能化的算法配置方法,改进依赖专家知识经验且繁琐耗时的手动算法配置方式,不仅提高了算法设计效率和求解问题时的性能,同时降低了算法的使用难度。