Marco Pavone

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Assistant Professor
Stanford University
Department of Aeronautics and Astronautics

Director, Autonomous Systems Laboratory
Assistant Professor (by courtesy), Department of Electrical Engineering
Assistant Professor (by courtesy), Institute for Computational and Mathematical Engineering
Assistant Professor (by courtesy), Information Systems Laboratory

Ph.D. Massachusetts Institute of Technology, 2010

Email: [last name]

Phone: (650) 723 4432

Dr. Marco Pavone is an Assistant Professor of Aeronautics and Astronautics at Stanford University, where he also holds courtesy appointments in the Department of Electrical Engineering, in the Institute for Computational and Mathematical Engineering, and in the Information Systems Laboratory. He is a Research Affiliate at the NASA Jet Propulsion Laboratory (JPL), California Institute of Technology. Before joining Stanford, he was a Research Technologist within the Robotics Section at JPL. He received a Ph.D. degree in Aeronautics and Astronautics from the Massachusetts Institute of Technology in 2010. Dr. Pavone’s areas of expertise lie in the fields of controls and robotics.

Dr. Pavone is a recipient of an NSF CAREER Award, a NASA Early Career Faculty Award, a Hellman Faculty Scholar Award, and was named NASA NIAC Fellow in 2011. At JPL, Dr. Pavone worked on the end-to-end optimization of the mission architecture for the Mars sample return mission. He has designed control algorithms for formation flying that have been successfully tested on board the International Space Station.

Dr. Pavone is the Director of the Autonomous Systems Laboratory (ASL). The goal of ASL is the development of methodologies for the analysis, design, and control of autonomous systems, with a particular emphasis on large-scale robotic networks and autonomous aerospace vehicles. The lab combines expertise from control theory, robotics, optimization, and operations research to develop the theoretical foundations for networked autonomous systems operating in uncertain, rapidly-changing, and potentially adversarial environments. Theoretical insights are then used to devise practical, computationally-efficient, and provably-correct algorithms for field deployment. Applications include robotic transportation networks, sensor networks, agile control of spacecraft during proximity operations, and mobility platforms for extreme planetary environments. Collaborations with NASA centers are a key component of the research portfolio.

Specifically, ASL's current research is along four main dimensions:

  • Cooperative control of robotic networks with application to future urban transportation systems and systems of unmanned aerial vehicles

  • Motion planning in dynamic and uncertain environments with application to autonomous spacecraft, self-driving cars, and drones

  • Unconventional space robotics, for the exploration of asteroids, comets, and other planetary bodies

  • Risk-sensitive and risk-constrained stochastic optimal control

The publications of the ASL lab are available here.


Stanford University, Department of Aeronautics & Astronautics

William F. Durand Building, Rm. 261

496 Lomita Mall

Stanford, CA 94305-4035