Meng Xi

Personal profile

Name:Meng Xi

Gender:Female

Degrees:Ph.D

Title:Lecturer

E-mail:mengxi@bjut.edu.cn

Research Areas

1. computational intelligence;

2. artificial neural networks;

3. intelligent modeling of complex industrial processes.

Publications

1 Meng Xi, Pawel Rozycki, Qiao Junfei*, Wilamowski Bogdan M*. Nonlinear system modeling using RBF networks for industrial application, IEEE Transactions on Industrial Informatics, 2018, 14(3):931-939.

2 Qiao Junfei*, Meng Xi, Li Wenjing. An incremental neuronal-activity-based RBF neural network for nonlinear system modeling, Neurocomputing, 2018, 302(8-9):1-11.

3 Qiao Junfei, Meng Xi*, Li Wenjing, Wilamowski Bogdan M. A novel modular RBF neural network based on a brain-like partition method. Neural Computing and Applications, 2020, 32(1): 899–911.

Personal Statement

Meng Xi received the Ph.D. degree in control science and engineering from Beijing University of Technology in 2018. She is currently a lecturer and postgraduate supervisor with the Faculty of Information Technology, Beijing University of Technology. She was a visiting scholar in 2016 with the Department of Electrical and Computer Engineering, Auburn University, USA. She has authored 10 scientific papers in international journals and conference proceedings.