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About

Remy Wehbe is a robotics and control systems researcher whose work sits at the intersection of multi-robot systems, probabilistic graph theory, and cybersecurity. His research focuses primarily on quantifying and optimizing the resilience and security of networked multi-robot systems (MRS) operating under uncertain or adversarial conditions — a critical challenge as autonomous robot teams are increasingly deployed in real-world environments. Wehbe's most significant contributions involve developing rigorous mathematical frameworks for probabilistic security and resilience. Beginning with foundational graph-theoretic security models in 2018, he progressively built toward more sophisticated approaches, including a convolutional neural network-based method for predicting security probabilities and combinatorial optimization techniques for bounding computational complexity. His 2021 work on probabilistic resilience, his most cited contribution with 12 citations, extended these ideas to dynamic systems subject to random communication failures. Most recently, he tackled the challenging problem of informative path planning under simultaneous communication uncertainty and adversarial attack. Across seven publications spanning 2018–2022, Wehbe has accumulated over 40 citations, establishing himself as an emerging voice in robust multi-robot coordination. His research offers practical tools for designing robot teams that remain functional and secure even when their communication networks are unreliable or compromised.