Ph.D. in Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT), 1999.
Professor Yehia Massoud's research focuses on the design of state-of-the-art innovative technological solutions that span over a broad range of technical areas including smart cities, autonomous systems, smart health, photonic metamaterials, and nanotechnology. Dr. Massoud's research group was responsible for developing the world’s first realization of compressive sensing systems for signals, which provided an unprecedented one order of magnitude savings in power consumption and significant reductions in size and cost and has enabled the implementation of self-powered sensors for smart cities and ultra-low power biomedical implantable devices.
Professor Yehia Massoud, a Fellow of the IEEE, holds a Ph.D. from the Massachusetts Institute of Technology (MIT), Cambridge, USA. He is currently the Director of the Innovative Technologies Laboratories (ITL) at KAUST. He was awarded the Rising Star of Texas Medal, and the DAC Fellowship. He received the US National Science Foundation CAREER Award, and the Synopsys Engineering Award. He was selected by the MIT EECS as one of ten featured alumni. He was also one of the fastest faculty to be granted tenure in the history of the Rice university. Dr. Massoud has been a PI or a Co-PI on more than $53 Million of funded research from the NSF, DOD, SRC, and the industry. He has published more than 475 papers in leading peer-reviewed journals and conferences.
N. Mahmood, J. Kim, M. Naveed, Y. Kim, J. Seong, S. Kim, T. Badloe, M. Zubair, M. Mehmood, Y. Massoud, and J. Rho, "Ultraviolet–Visible Multifunctional Vortex Metaplates by Breaking Conventional Rotational Symmetry," Nano Letters, 2023.
A. Hamrouni, T. Alelyani, H. Ghazzai, and Y. Massoud, “Toward Collaborative Mobile Crowdsourcing“, IEEE Internet of Things Magazine, 2022.
A. Goyal, A. Kumar, and Y. Massoud," Thermal Stability Analysis of Surface Wave Assisted Bio-Photonic Sensor," Photonics, 2022.
D. Divyanshu, R. Kumar, D. Khan, S. Amara, and Y. Massoud, “Physically Unclonable Function using GSHE driven SOT assisted p-MTJ for next generation hardware security applications”, IEEE Access, 2022.
M. Lucic, H. Ghazzai, C. Lipizzi, and Y. Massoud, “Integrating County-Level Socioeconomic Data for COVID-19 Forecasting in the United States“, IEEE Open Journal of Engineering in Medicine and Biology, 2021.