Signal Processing, Learning, and Communication Systems
In wireless communications, we seek to transfer information over increasingly difficult conditions, harsh environments, and vulnerable channels. The countless "smart things" pervading our lives drive evermore-exigent scenarios and present new challenges constantly. The curriculum for the ECE MEng with an emphasis in Wireless Communications covers a wide variety of fundamental coursework and the relevant project experience to enable graduates to conceive, design, analyze, develop, secure, and field state-of-the-art wireless communication systems that connect us on a global scale.
Courses
ECE 5984 SS: R&D Methods for Engineers (3) Fall
ECE 5984 SS: Applications of Machine Learning (3) Spring
ECE 5984 SS: Math Methods for ECE (3) Fall
ECE 5944: ECE Graduate Seminar (1+1) Both
ENGE 5304: Grad Student Success in Multicultural Environments (1) Both
ECE 4524: Artificial Intelligence and Engineering Applications (4) Both
ECE 4560: Computer and Network Security (3) Both
ECE 4564: Network Application Design (3) Both
ECE 4580: Digital Image Processing (3) Both
ECE 4644: Satellite Communications (3) Spring
ECE 5424: Advanced Machine Learning (3) Both
ECE 5434: Cyber-Physical Systems (3) Spring
ECE 5620: Advanced DSP & Filter Design (3) Spring
ECE 5635: Radar Systems Analysis and Design (3) Fall
ECE 5664: Cellular Communication Systems (3) Spring
ECE 5805-5806: Graduate Design Project (6) Both
or
ECE 5904: Project & Report (3) B
and
another Depth course from above
Sample Curriculum
Signal Processing, Learning, and Communication Systems – Washington, D.C. Metro Area Faculty Profiles
Collegiate Assistant Professor of ECE
Dr. Mary Lanzerotti is a Collegiate Assistant Professor with the Virginia Tech Bradley Department of Electrical and Computer Engineering in Northern Virginia as of August 2020. Prior to joining Virginia Tech, she was an Assistant Professor at the United States Military Academy in West Point, New York. She is also an Adjunct faculty member at Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio, where she worked previously. She has held positions at IBM Thomas J. Watson Research Center, where she was integrator of the POWER4TM microprocessor Instruction Fetch Unit and co-author of the POWER6 introduction paper at IEEE International Solid-States Circuits Conference. She is inventor or co-inventor of six patents. She is an ABET program evaluator in Electrical Engineering and is Senior Member of the IEEE. She and her colleagues received the 2016 Dan Repperger Best Paper Award at IEEE National Aeronautics and Electronics Conference for their research on error in parameter estimation in a multi-tier weak radio signal detection process. She is a member of the American Physical Society, IEEE Photonics Society, and IEEE Women in Engineering. She received M.S. and Ph.D. degrees from Cornell University, M. Phil. degree from University of Cambridge, United Kingdom, where she was a Churchill Scholar, and A.B. degree summa cum laude from Harvard University.
Dr. Lanzerotti’s Google Scholar profile.
Research Interests:
- Signal processing, weak radio frequency signal estimation, VLSI, bursting of thick liquid fluid films, swing stabilization for MEDEVAC rescues
ECE Graduate Courses:
- ECE 5605: Stochastic Signals and Systems