Dr. Christopher Ratto is a senior staff engineer whose research interests include generative models, few- shot object recognition, and deep reinforcement learning. An electrical engineer by training, he has expertise in machine learning, signal and image processing, and remote sensing. He developed several algorithms for exploiting remote sensing data, including electro-optic and synthetic aperture radar data that have transitioned to operations. He also contributed to computational neuroscience research demonstrating semantic neural signal decoding of visual neural stimuli and developed novel Bayesian techniques for classifying high-dimensional data on the basis of feature cost. Dr. Ratto developed an internal course on machine learning, taken by about 50 APL staff members per year since 2016. Additional areas of expertise include artificial intelligence vulnerabilities and defenses, applied neuroscience and neuroengineering, and machine vision and perception.
Ph.D., Electrical and Computer Engineering
M.S., Electrical and Computer Engineering
Catholic University of America