CV Research Bio

Clinton Enwerem
Doctoral Student and Researcher in Systems and Control


I am an Electrical & Computer Engineering Ph.D. student at the University of Maryland (UMD), College Park, MD, USA, where I am advised by Professor John S. Baras, who holds the positions of Distinguished University Professor and Endowed Lockheed Martin Chair in Systems Engineering. My research interests lie broadly at the nexus of control theory, multiagent systems, and robotics. At UMD, I am affiliated with the Institute for Systems Research and the Systems Engineering & Integration Lab. I have also received the Dean's Fellowship from the Graduate School at UMD and the Microsoft Diversity in Robotics and Autonomy PhD Fellowship from a partnership between Microsoft Corporation and the Maryland Robotics Center.

Before UMD

Prior to resuming doctoral studies at UMD, I completed a year-long stint as a robotics trainee at Nigeria's foremost robotics and AI research center — Robotics and Artificial Intelligence Nigeria (RAIN). At RAIN, I worked with Dr. Olusola Ayoola on varied projects spanning robot navigation, visual SLAM, and robot control. Before that, in affiliation with the Electrical Engineering Department at my alma mater, I collaborated with Ihechiluru Okoro on research topics at the intersection of robust control, observer-based compensator design, and feedback control of time-delayed dynamical systems.


I earned my undergraduate degree in Electrical Engineering from the University of Nigeria, working under the supervision of Dr. Udoka Nwaneto. My bachelor's thesis focused on model-based controller design for speed regulation in electric drives.


Contact Info

2239 A.V. Williams Bldg.

8223 Paint Branch Dr

College Park, MD 20740

me at clintonenwerem dot com


  • [paper] One paper accepted for presentation at ECC'24.

  • [paper] One paper accepted to the IEEE-LCSS journal.

  • [talk] I gave a talk on our paper titled "Consensus-Based Leader-Follower Formation Tracking for Control-Affine Nonlinear Multiagent Systems" at CoDIT 2023.

  • [paper] Our paper on "Consensus-Based Leader-Follower Formation Tracking for Control-Affine Nonlinear Multiagent Systems" has been accepted for presentation at CoDIT'23.

  • [award] I received the Microsoft Diversity in Robotics & Autonomy PhD Fellowship for the 2022-2023 academic term, sponsored by a joint award from Microsoft and the Maryland Robotics Center.

  • [internship] May-Aug. 2022: Summer 2022 research internship conducted at USMSM and UMD, with Dr. Danilo Romero and in collaboration with the MATRIX Lab. Focus: Multi-robot cooperative control under sensor uncertainty.


I study the coordination and control of networked, intelligent, embodied, and possibly heterogeneous collectives in dynamic and partially-observed environments, using mathematical tools from graph theory, control theory, learning theory, and optimization. My focus is on developing techniques for safe and robust autonomy under uncertainty, beginning with such representative problems as formation tracking, dynamic consensus, robust motion planning and decision making, and safety-critical collective control, drawing examples from the robotics literature and related fields.


Submitted/In Review

Clinton Enwerem, Erfaun Noorani, John S. Baras, and Brian M. Sadler, Robust Stochastic Shortest-Path Planning via Risk-Sensitive Incremental Sampling, 2024.


Clinton Enwerem and John S. Baras, Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions. To appear in the proceedings of the 2024 European Control Conference.

Clinton Enwerem and John S. Baras, Formation Tracking for a Class of Uncertain Multiagent Systems: A Distributed Kalman Filtering Approach, IEEE Control Systems Letters, Volume 8, 2024.


Clinton Enwerem and John S. Baras, “Consensus-Based Leader-Follower Formation Tracking for Control-Affine Nonlinear Multiagent Systems,” in the 9th International Conference on Control, Decision and Information Technologies (CoDIT), Rome, Italy: IEEE, Jul. 2023, pp. 1226–1231. doi: 10.1109/CoDIT58514.2023.10284199.


Peer Review: MED'23, ECC'24, Heliyon.