Jonathan P. How is the Richard C. Maclaurin Professor of Aeronautics and Astronautics at the Massachusetts Institute of Technology. He received a B.A.Sc. (aerospace) from the University of Toronto in 1987, and his S.M. and Ph.D. in Aeronautics and Astronautics from MIT in 1990 and 1993, respectively, and then studied for 1.5 years at MIT as a postdoctoral associate. Prior to joining MIT in 2000, he was an assistant professor in the Department of Aeronautics and Astronautics at Stanford University.
Dr. How was the editor-in-chief of the IEEE Control Systems Magazine (2015-19) and is an associate editor for the AIAA Journal of Aerospace Information Systems and the IEEE Transactions on Neural Networks and Learning Systems. He was an area chair for International Joint Conference on Artificial Intelligence (2019) and will be the program vice-chair (tutorials) for the Conference on Decision and Control (2021). He was elected to the Board of Governors of the IEEE Control System Society (CSS) in 2019 and is a member of the IEEE CSS Technical Committee on Aerospace Control and the Technical Committee on Intelligent Control. He is the Director of the Ford-MIT Alliance and was a member of the USAF Scientific Advisory Board (SAB) from 2014-17.
His 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. His work has been recognized with multiple awards, including 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 IEEE Control Systems Society Video Clip Contest, the IROS Best Paper Award on Cognitive Robotics (2017 and 2019) and three AIAA Best Paper in Conference Awards (2011-2013). He was awarded the Air Force Commander's Public Service Award (2017) for his contributions to the SAB. He is a Fellow of IEEE and AIAA.
B.A.Sc., 1987, University of Toronto S.M., 1990, Massachusetts Institute of Technology Ph.D., 1993, Massachusetts Institute of Technology
Honors and Awards
2020 — Winner, ICRA Best Paper Award in Service Robotics; 2020 — Elected to the Board of Governors of the IEEE Control System Society; 2020 — AIAA Intelligent Systems Award; 2019 — Winner, IROS Best Paper Award on Cognitive Robotics sponsored by KROS; 2019 — Finalist, IROS Best Paper Award on Safety, Security, and Rescue Robotics in memory of Motohiro Kisoi; 2019 — AUVSI XCELLENCE Humanitarian Award (joint with NASA); 2019 — Co-author for Outstanding Student Paper Honorable Mention at AAAI-19; 2018 — Finalist for ICRA Best Multi-Robot Systems Paper Award; 2018 — Elevated to IEEE Fellow; 2017 — Department of the Air Force Commander's Public Service Award; 2017 — Winner of IROS Best Student Paper Award (co-author); 2017 — Finalist for IROS Best Paper Award on Cognitive Robotics; 2017 — Finalist for ICRA Best Multi-Robot Systems Paper Award; 2016 — Elevated to AIAA Fellow; 2015 — AeroLion Technologies Outstanding Paper Award, given for paper A. N. Kopeikin, S. S. Ponda, L. B. Johnson, J. P. How, "Dynamic Mission Planning for Communication Control in Multiple Unmanned Aircraft Teams", Unmanned Systems, Vol. 1, No. 1 (2013), 41–58; 2015 — First place in the Second IEEE Control Systems Society Video Clip Contest; 2015 — Finalist for best paper award at RSS 2015; 2015 — Best paper in NIPS workshop on multiagent systems; 2015 — Finalist for ``Best project in 2015'' award from the MIT Lincoln Laboratory Advanced Concepts Committee; 2014 — AIAA Intelligent Systems best paper presented at the 2013 AIAA Infotech@Aerospace conference (``Robust Trajectory Planning for Autonomous Parafoils under Wind Uncertainty'' by Luders et al.); 2013 — AIAA Best Paper Award from 2012 Guidance Navigation and Control Conference by the AIAA Guidance, Navigation and Control Technical Committee (``Experimental demonstration of efficient multi-agent learning and planning for persistent missions in uncertain environments'' by N. Ure et al.); 2013 — Finalist for the Best Cognitive Robotics Paper Award at ICRA for paper ``Reinforcement Learning with Misspecified Model Classes'' by J. Joseph et al.; 2012 — recipient of the AIAA Best Paper Award from the 2011 Guidance Navigation and Control Conf.by the AIAA Guidance, Navigation and Control Technical Committee for the paper "Decentralized Information-Rich Planning and Hybrid Sensor Fusion for Uncertainty Reduction in Human-Robot Missions'' by S. Ponda et al.; 2011 — Awarded prize for the "Best Applications paper published in Automatica over the past three years" for paper H.L. Choi and J.P. How, "Continuous trajectory planning of mobile sensors for informative forecasting," Vol. 46, Issue 8, Pages 1266-1275; 2011 — National Instruments Graphical System Design Achievement Award (Education category); 2009 — appointed Richard C. Maclaurin Professor of Aeronautics and Astronautics at MIT; 2008 — Boeing Special Invention Award; 2007 — Best Paper Presentation at 100th Meeting of the Aerospace Control and Guidance Systems Committee; 2006-2008 - Raymond L. Bisplinghoff Fellow for MIT AeroAstro Department; 2000-2002 — Boeing Associate Professor, MIT; 2002 — Burka Award for outstanding achievement in the preparation of papers contributing to the advancement of navigation and space guidance; 1997-1999 — Charles Powell Faculty Scholar, Stanford Univ.; 1995 - NASA Certificate of Appreciation for MACE; 1994-1997 — Davis Faculty Scholar, Stanford University.
American Institute of Aeronautics and Astronautics, Fellow; Institute of Electrical and Electronics Engineers, Fellow
Positions Held at MIT
7/09 - present Richard C. Maclaurin Professor of Aeronautics and Astronautics
7/07 - 6/09 Professor of Aeronautics and Astronautics, MIT
4/00 - 6/07 Associate Professor, Department of Aeronautics and Astronautics, MIT, (Tenured in 2003)
2/93 - 8/94 PostDoctoral Associate, Department of Aeronautics and Astronautics, MIT
Specialization and Research Interests
Navigation and control; design and implementation of distributed robust planning algorithms to coordinate multiple autonomous vehicles in dynamic uncertain environments; adaptive flight control to enable autonomous agile flight and aerobatics; experimental and theoretical robust control
Feedback control, navigation and estimation, optimal control