Marcus Smith
About Marcus Smith
Marcus Smith is an R&D Engineer at Sandia National Laboratories with extensive experience in electrical engineering, specializing in wireless power technologies and smart grid automation.
Current Position at Sandia National Laboratories
Marcus Smith has been working as an R&D Engineer at Sandia National Laboratories since 2012. Based in the Albuquerque, New Mexico area, his role involves extensive research and development activities. His work focuses on advanced technological innovations, contributing to various projects within the laboratory.
Previous Experience at Air Force Research Laboratory
Before joining Sandia National Laboratories, Marcus Smith held the position of Engineering Lead at the Air Force Research Laboratory. He worked on various projects from 2009 to 2012 at Tyndall AFB, FL, where his responsibilities included leading engineering teams and developing new technologies for the Air Force.
Educational Background in Electrical Engineering
Marcus Smith holds a PhD in Electrical Engineering from the University of Florida, completed in 2014. His doctoral research was centered on the design and analysis of microwave rectifying antenna structures and related circuits. Additionally, he has a Master’s degree and a Bachelor’s degree in Electrical Engineering from Utah State University, obtained in 2006 and 2005, respectively.
Expertise in Wireless Power Technologies
Marcus Smith specializes in the remote powering of unmanned ground vehicles and security sensor platforms using wireless power technologies. His research includes developing and optimizing systems for efficient wireless power transfer, contributing significantly to advancements in these fields.
Skills in Software and Circuit Design
Marcus Smith is proficient in various software development tools, including MATLAB, Simulink, VB, C, C++, Labview, and FORTRAN. His expertise extends to circuit design and modeling using PSCAD, OrCAD Capture, PSPICE, and Tanner Tools. Additionally, he is skilled in statistical analysis and modeling, utilizing JMP and Excel for data interpretation.