Research Interests
Control theory, optimization, and learning; in particular, robotics and autonomous systems, networked and distributed control systems, and cyber-physical systems.
Bio
Michael M. Zavlanos research focuses on control theory, optimization, learning, and AI and, in particular, autonomous systems and robotics, networked and distributed control systems, and cyber-physical systems.
Education
- Ph.D. University of Pennsylvania, 2008
Positions
- Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
- Professor in the Department of Electrical and Computer Engineering
- Professor in Computer Science
- Associate of the Duke Initiative for Science & Society
Awards, Honors, and Distinctions
- Young Investigator Program Award. Office of Naval Research. 2014
- Faculty Early Career Development (CAREER) Program. National Science Foundation. 2012
- Faculty Early Career Development (CAREER) Program. National Science Foundation. 2011
Courses Taught
- ME 627: Linear System Theory
- ME 592: Research Independent Study in Mechanical Engineering or Material Science
- ME 591: Research Independent Study in Mechanical Engineering or Material Science
- ME 391: Undergraduate Projects in Mechanical Engineering
- ECE 391: Projects in Electrical and Computer Engineering
- CEE 627: Linear System Theory
In the News
- Bringing Order to the ‘Wild West’ of Artificial Intelligence in Medicine (Jan 2…
- Duke Adds 21 Faculty to Distinguished Faculty Rank (May 7, 2019)
- Four Faculty Named Distinguished Professors (Jun 29, 2018)
Representative Publications
- Kantaros, Y., and M. M. Zavlanos. “Sampling-based optimal control synthesis for multirobot systems under global temporal tasks.” IEEE Transactions on Automatic Control 64, no. 5 (May 1, 2019): 1916–31. https://doi.org/10.1109/TAC.2018.2853558.
- Ma, W. J., C. Oh, Y. Liu, D. Dentcheva, and M. M. Zavlanos. “Risk-averse access point selection in wireless communication networks.” IEEE Transactions on Control of Network Systems 6, no. 1 (March 1, 2019): 24–36. https://doi.org/10.1109/TCNS.2018.2792309.
- Guo, M., and M. M. Zavlanos. “Probabilistic Motion Planning Under Temporal Tasks and Soft Constraints.” IEEE Transactions on Automatic Control 63, no. 12 (December 1, 2018): 4051–66. https://doi.org/10.1109/TAC.2018.2799561.
- Freundlich, C., Y. Zhang, and M. M. Zavlanos. “Distributed Hierarchical Control for State Estimation with Robotic Sensor Networks.” IEEE Transactions on Control of Network Systems 5, no. 4 (December 1, 2018): 2023–35. https://doi.org/10.1109/TCNS.2017.2782481.
- Lee, S., and M. M. Zavlanos. “Approximate projection methods for decentralized optimization with functional constraints.” IEEE Transactions on Automatic Control 63, no. 10 (October 1, 2018): 3248–60. https://doi.org/10.1109/TAC.2017.2778696.