Michael Zavlanos

Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science

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.

Appointments and Affiliations

  • Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
  • Professor in the Department of Electrical and Computer Engineering
  • Associate Professor of Computer Science
  • Associate of the Duke Initiative for Science & Society

Contact Information

  • Office Location: Wilkinson Building, Room 417, Durham, NC 27708
  • Office Phone: (919) 660-5528
  • Email Address: michael.zavlanos@duke.edu
  • Websites:

Education

  • Ph.D. University of Pennsylvania, 2008

Research Interests

Control theory, optimization, and learning; in particular, robotics and autonomous systems, networked and distributed control systems, and cyber-physical systems.

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

  • ECE 291: Projects in Electrical and Computer Engineering
  • ME 758S: Curricular Practical Training

In the News

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.
  • 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.
  • 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.
  • 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.