Rate My Professor Jie Xu

Professor Jie Xu serves as Chair and Professor of Electrical and Computer Engineering in the Seaver College of Science and Engineering at Loyola Marymount University, where he joined the faculty in 2009. He holds a B.S. degree from Tianjin University in 2000, an M.S. degree from Tianjin University in 2003, and a Ph.D. from the University of Massachusetts Amherst in 2008. Prior to pursuing his doctoral studies, Dr. Xu worked as a software engineer at Zhongxing Telecommunications Equipment Co. Ltd. in China, participating in the development of system software for the IS-2000 1X CDMA cellular system. At Loyola Marymount University, he teaches courses in the communications area of the curriculum and leads the Electrical and Computer Engineering Department, located in Doolan Hall 204.

Dr. Xu's research specializations include electromagnetics, wave propagation in complex media, antenna design, and their applications in wireless communications, remote sensing, and biomedical imaging. His ongoing and recent projects encompass early breast cancer detection with microwave imaging, functional dimensions of electromagnetic fields in scattering environments to assess diversity benefits from field polarizations, characteristics of singular modes of antenna arrays for beam-forming and object locating, formulation of scattering-inclusive dyadic Green's function and its angular radiation spectrum, orbital angular momentum of beamed electromagnetic waves for wireless spatial multiplexing, and characteristic modes of material bodies for special-purpose antenna design. Key publications feature "Zernike-Polynomial-Based Entire-Domain Vector Basis Functions for Circular Domains" published in IEEE Transactions on Antennas and Propagation in 2022, "Generation of Laguerre-Gaussian Modes by Aperture or Array Sources" in the same journal in 2019, "Characteristic Modes of Circular Conducting Plate with Zernike Polynomials as Entire-Domain Basis" presented at the 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, and "Object Localization Using Machine Learning" at the 2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting. Additional works include conference contributions such as "Degrees of freedom of OAM-based line-of-sight radio systems" in 2017 and various papers on angular spectra and Green's functions in random scattering environments from 2010 to 2015.