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Michael Zavlanos

Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
Thomas Lord Department of Mechanical Engineering and Materials Science
Wilkinson Building, Room 417, Durham, NC 27708
Wilkinson Building, Room 417, Durham, NC 27708

Overview


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.

Current Appointments & Affiliations


Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science · 2022 - Present Thomas Lord Department of Mechanical Engineering and Materials Science, Pratt School of Engineering
Professor in the Department of Electrical and Computer Engineering · 2022 - Present Electrical and Computer Engineering, Pratt School of Engineering
Professor in Computer Science · 2024 - Present Computer Science, Trinity College of Arts & Sciences
Associate of the Duke Initiative for Science & Society · 2017 - Present Duke Science & Society, University Initiatives & Academic Support Units

In the News


Published January 23, 2023
Bringing Order to the ‘Wild West’ of Artificial Intelligence in Medicine
Published May 7, 2019
Duke Adds 21 Faculty to Distinguished Faculty Rank
Published June 29, 2018
Four Faculty Named Distinguished Professors

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Recent Publications


Sampling-based optimal control synthesis for multirobot systems under global temporal tasks

Journal Article IEEE Transactions on Automatic Control · May 1, 2019 This paper proposes a new optimal control synthesis algorithm for multirobot systems under global temporal logic tasks. Existing planning approaches under global temporal goals rely on graph search techniques applied to a product automaton constructed amon ... Full text Cite

Risk-averse access point selection in wireless communication networks

Journal Article IEEE Transactions on Control of Network Systems · March 1, 2019 This paper considers the problem of selecting the optimal set of access points and routing decisions in wireless communication networks. We consider networks that are subject to uncertainty in the wireless channel, for example, due to multipath fading effe ... Full text Cite

Distributed Hierarchical Control for State Estimation with Robotic Sensor Networks

Journal Article IEEE Transactions on Control of Network Systems · December 1, 2018 This paper addresses active state estimation with a team of robotic sensors. The states to be estimated are represented by spatially distributed, uncorrelated, stationary vectors. Given a prior belief on the geographic locations of the states, we cluster t ... Full text Cite
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Recent Grants


Center of Excellence: Assured Autonomy in Contested Environments

ResearchCo-Principal Investigator · Awarded by University of Florida · 2019 - 2026

GuArDIAN: General Active Sensing for conDItion AssessmeNt

ResearchCo-Principal Investigator · Awarded by Department of Energy · 2019 - 2023

CPS: Small: Distributed Learning and Control of Cyber-Physical Systems

ResearchPrincipal Investigator · Awarded by National Science Foundation · 2019 - 2023

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Education, Training & Certifications


University of Pennsylvania · 2008 Ph.D.

External Links


Personal Webpage