Jason Lohn-Silicon Valley Campus - Carnegie Mellon University

lohn

Contact Info:
Jason Lohn
Carnegie Mellon University
Silicon Valley
Building 23 (MS23-11)
Moffett Field, CA 94035

Office: B23 #201B
Phone: 650-335-2802
Email: jason.lohn@sv.cmu.edu
Research Group: Automated Hardware Design & Synthesis


Jason Lohn
Associate Research Professor
Director, Carnegie Mellon Innovations Laboratory

Areas of Interest

Hardware design and optimization algorithms, Mobile device optimization, Antenna Synthesis and Optimization, Energy efficiency optimization, Scheduling systems

Overview

Dr. Lohn is an Associate Research Professor in Electrical and Computer Engineering at Carnegie Mellon University. He has worked at Google, NASA Ames Research Center, Stanford University, and IBM Corporation. He received his M.S. and Ph.D. in Electrical Engineering from the University of Maryland at College Park and his B.S. in Electrical Engineering from Lehigh University. He leads research in Evolvable Systems at Carnegie Mellon and NASA Ames and is closely affiliated with the growing field called evolvable hardware -- the study of how stochastic search algorithms can be used to design and configure electronic and mechanical hardware. He co-founded and chaired a series of successful NASA/DoD evolvable hardware workshops and conferences. He led a team of scientists and engineers to successfully evolve, develop and fly three evolved X-band antennas in space aboard NASA's Space Technology 5 mission in 2006.

His main interests are to research and develop search algorithms that can automatically design and optimize hardware systems to achieve increased performance and reliability in application areas such as antenna design, microelectromechanical systems, robotics, and spacecraft design.  He has co-founded a Silicon Valley startup company called X5 Systems to commercialize his work on advanced antenna synthesis and optimization algorithms.  Dr. Lohn is a member of the IEEE, ACM, Sigma Xi, and Phi Kappa Phi. He has over 50 technical publications and has made contributions in automated hardware design, self-replicating systems, parallel processing, and neural networks. Dr. Lohn serves as an Associate Editor of IEEE Transactions on Evolutionary Computation.