Jonathan P. How
Department of Aeronautics and Astronautics Massachusetts Institute of Technology;Aerospace Controls Laboratory, Massachusetts Institute of Technology
Dr. How’s research focuses on robust planning and learning under uncertainty with an emphasis on multiagent systems, and he was the planning and control lead for the MIT DARPA Urban Challenge team in 2007. His work has been recognized with multiple awards, including the 2020 IEEE CSS Distinguished Member Award, the 2020 AIAA Intelligent Systems Award, the 2002 Institute of Navigation Burka Award, the 2011 IFAC Automatica award for best applications paper, the 2015 AeroLion Technologies Outstanding Paper Award for Unmanned Systems, the 2015 winner of the IEEE Control Systems Society Video Clip Contest, the IROS Best Paper Award on Cognitive Robotics (2017 and 2019), the 2020 ICRA Best Paper Award in Service Robotics, and three AIAA Best Paper in Conference Awards (2011-2013). He received the Amazon Machine Learning Research Award in 2018 and 2020, and he was awarded the Air Force Commander’s Public Service Award in 2017 for his contributions to the SAB.
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