Warren’s research interests are in large area, inexpensive, flexible electronics such as amorphous silicon and metal oxide devices. He is interested in using machine learning near the sensors and actuators to enable adaptive data acquisition and actuation for control systems, low-cost, low-energy sensing, adaptable MEMS devices, and new imaging methods for biological and robotics applications.
His previous work at Hewlett Packard Laboratories includes resistive RAM, memory side accelerators, roll-to-roll imprinted electronics, model predictive control, and 3D imaging for immersive experiences. He also developed methods for task-based evaluation image quality and human vision modeling for image system design, hype redundant control systems, smart sensors, and investigation of instabilities in amorphous solar cells.
Warren has over 250 publications and 100 granted patents. He is a Fellow of the American Physics Society and Senior Member of the IEEE. He was a Distinguished Technologist at HP Labs and received a number of best paper awards in printed electronics and hydrogen in silicon.
Dr. Jackson holds a Ph.D. and M.S. in physics from University of California at Berkeley, and a B.S. in Physics, Math, and Applied Math from Stanford.