Antenna Optimization Technology and Applications
Monday May 23, 2:00 pm, Bldg 23, Rm 109
Jason D. Lohn, Associate Research Professor, Dept of Electrical and Computer Engineering, CMUSV
Summary: Current methods of designing and optimizing antennas by hand are time and labor intensive, limit complexity, and require significant expertise and experience. New AI algorithms can overcome these limitations by automatically searching the design space and finding effective solutions that are closer to limits imposed by physics. For example, our algorithms have discovered antenna designs that have wide impedance bandwidth, are electrically small, highly efficient, and compare well in terms of size, weight, and cost. While optimization modules are commonly available in commercial antenna CAD tools, they are typically simple parametric methods, and no system yet offers an antenna synthesis capability. We discuss the antenna synthesis system we are developing and its use in a variety of applications, including disaster management scenarios where portability, reliability, and high performance are required.
Presentation slides (.pdf)
About the speaker: Jason Lohn is an Assoc. Research Professor at Carnegie Mellon Silicon Valley. Previously he led Evolvable Systems research at NASA Ames Research Center, worked in search quality at Google, was a Visiting Scholar at Stanford, and worked as a engineer at IBM. He received his MS and PhD in Electrical Engineering from the University of Maryland at College Park, and his BS in Electrical Engineering from Lehigh University. He has over 50 technical publications and his work has been featured in Wired magazine, MIT Tech Review, and Popular Science. He was a co-founder and co-chair of six NASA/DoD Conferences on Evolvable Hardware, and serves as an Associate Editor of IEEE Transactions on Evolutionary Computation.