Lijia Chen

Lijia Chen is an Associate Professor of Communication Engineering in the School of Physics and Electronics, Henan University, Henan Province, China. At present, Dr. Chen is the leader of the first-class specialty and excellent engineer pilot specialty of communication engineering in Henan Province, the leader of the excellent experimental class of communication engineering, the member of the innovation team of Henan Province, and the deputy director of the experimental teaching center of electronic and communication engineering in Henan Province. Director of Kaifeng Intelligent Manufacturing Engineering Technology Research Center, member of Henan Communication Society and member of Henan intelligent manufacturing Committee. In addition, he is serving as Director of Graduate Studies in Detection Technology and Automation, head of Communication Engineering, and member of the research group in the Laboratory of advanced computation methods and intelligent applications. His research interests are in Evolutionary Computation, Communication Network, Digital Signal Processing and Evolutionary Design Methods on Electronic Circuits and Systems. He has published over 20 journal papers, over 10 conference papers and 7 granted patents.

Publications

Technologies to Advance Automation in Forensic Science and Criminal Investigation
Chung-Hao Chen, Wen-Chao Yang, Lijia Chen. © 2022. 289 pages.
Within modern forensic science and criminal investigation, experts face several challenges including managing huge amounts of data, handling miniscule pieces of evidence in a...
Polynomial Approximation for Two Stage Stochastic Programming with Separable Objective
Lijia Chen, Dustin J. Banet. © 2012. 12 pages.
In this paper, the authors solve the two stage stochastic programming with separable objective by obtaining convex polynomial approximations to the convex objective function with...
Polynomial Approximation for Two Stage Stochastic Programming with Separable Objective
Lijia Chen, Dustin J. Banet. © 2010. 14 pages.
In this paper, the authors solve the two stage stochastic programming with separable objective by obtaining convex polynomial approximations to the convex objective function with...