Areas of Research: nonlinear control and dynamical systems.
D234 Engineering Quadrangle
Naomi Ehrich Leonard is the Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering and an associated faculty member of the Program in Applied and Computational Mathematics at Princeton University where she has been since 1994. In 2004 she was awarded a John D. and Catherine T. MacArthur Foundation Fellowship. In 2007 the Institute for Electrical and Electronic Engineers (IEEE) named her an IEEE Fellow. She has also received the University of California at Santa Barbara’s Mohammed Dahleh Distinguished Lecture Award (2005), the Automatica Prize Paper award (1999), the Office of Naval Research Young Investigator Award (1998) and the National Science Foundation CAREER Award (1995). In 2001 she was the Lise Meitner Guest Professor at Lund University, Sweden and in 2007 a Visiting Professor at University of Pisa, Italy. She has delivered several plenary lectures at conferences including the IEEE International Conference on Robotics and Automation (ICRA) in 2008, International Symposium on Mathematical Theory of Networks and Systems (MTNS) in 2008, IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles in 2008, SIAM Conference on Control and Its Applications in 2005, SIAM Conference on Applications of Dynamical Systems in 2003 and the IFAC Nonlinear Control Systems Design Symposium (NOLCOS) in 1998. She teaches undergraduate and graduate courses in dynamics and control. Her research group includes graduate students, postdoctoral researchers as well as undergraduates. She has served as associate editor for Automatica and SIAM Journal on Control and Optimization. She received the B.S.E. degree in mechanical engineering from Princeton University in 1985. From 1985 to 1989, she worked as an engineer in the electric power industry. She received the M.S. and Ph.D. degrees in electrical engineering from the University of Maryland in 1991 and 1994.
Professor Leonard specializes in a branch of engineering and applied mathematics called control theory. The field involves designing and analyzing methods for influencing the behavior of complex, dynamical systems using feedback. Feedback refers to adjustments in actions taken by a system in response to measurements of the system’s own state; feedback is critical for performance and robustness in self-regulating engineered systems and, for the very same reasons, feedback is ubiquitous in biological systems at every scale. In recent years, Leonard has been interested in coordinated control of mobile, multi-agent systems in engineering (robotic teams) and in nature (animal groups). A central goal is using formal analysis to understand and to derive the means for collective motion, collective sensing and collective decision-making from the responsive behavior of individual agents to their environment and to the behavior of other agents in the group. She applies this research to a new kind of automated and adaptive ocean observing system that consists of a coordinated network of underwater robotic vehicles that carry sensors to collect scientific data in the ocean; this work has exciting implications for contributing to a better understanding of our changing environment. She co-leads a large, collaborative effort called Adaptive Sampling and Prediction that featured a major field experiment in Monterey Bay, California in August 2006 and built off an earlier major field experiment also in Monterey Bay in August 2003. Using similar mathematical concepts and tools from control theory, Leonard collaborates with biologists to study fish schooling, seeking to help understand the coupled roles of feedback, information flow and spatial dynamics in collective behavior and decision-making in the school. She is interested in the joint challenge to explain the enabling mechanisms in animal groups and to define provable mechanisms for robotic groups. Her approach with her collaborators is an integrated one: formal bio-inspired models and analysis tools derived to synthesize collective robotic behavior can be used to evaluate design hypotheses for animal groups; subsequent revelations from the biology will in turn inspire new strategies for robotic systems. Leonard also works in collaboration with engineers, applied mathematicians, and cognitive and social psychologists to investigate decision dynamics in mixed teams of humans and robots, exploring how humans and robots can best jointly contribute to complex decision-making problems.
- Collective decision-making in ideal networks: The speed-accuracy tradeoff. IEEE Transactions on Control of Network Systems (with V. Srivastava)
- Modeling human decision-making in generalized Gaussian multi-armed bandits. Proceedings of the IEEE (with P. Reverdy and V. Srivastava)
- Adaptive network dynamics and evolution of leadership in collective migration. Physica D (with D. Pais)
View Complete Publications list.