Mouhyemen Khan

Qatar University, Georgia Institute of Technology

Papers

Total Citations

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About

Mouhyemen Khan is a researcher whose work lies at the intersection of safe autonomous systems, control theory, and cyber-physical systems. His key research areas include mobile sensor networks, safety-critical control, and the integration of learning with formal safety guarantees. Khan's most cited work, "Mobile Target Coverage and Tracking on Drone-Be-Gone UAV Cyber-Physical Testbed" (2017, 73 citations), addresses the challenge of using low-cost mobile robots equipped with sensors for environmental monitoring and surveillance. This paper demonstrates how mobile wireless sensor networks can be deployed for rapid and inexpensive target coverage tasks, contributing to the practical application of UAV-based sensing. In his more recent influential work, "Gaussian Control Barrier Functions: Safe Learning and Control" (2020, 13 citations), Khan tackles a fundamental problem in modern autonomy: ensuring safety despite model uncertainty. By introducing Gaussian processes into control barrier functions, he provides a framework that maintains safety guarantees even when the system's mathematical model is imperfect. This contribution is particularly significant for autonomous systems operating in unpredictable real-world environments, bridging the gap between theoretical safety guarantees and practical deployment.