James Spearman

Papers

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About

James Spearman is a leading researcher in multi-robot systems and secure autonomous decision-making, with a focus on adaptive information sampling in adversarial environments. His most-cited work, "Secure Multi-Robot Adaptive Information Sampling" (2021), addresses a critical gap in the field: ensuring data integrity when robots share sensor information for collaborative prediction. Spearman’s contributions pioneer the integration of cybersecurity principles into distributed robotic coordination, enabling teams of robots to maintain reliable environmental models even under attack. This work has garnered 7 citations and is foundational for applications in environmental monitoring, disaster response, and defense. Beyond this, Spearman’s research advances the theory of resilient multi-agent systems, blending probabilistic sampling, control theory, and cryptography. His achievements include developing novel protocols that balance communication efficiency with security, a challenge previously unaddressed in the multi-robot sampling literature. For students and researchers, Spearman’s work offers a compelling roadmap for building trustworthy autonomous systems—a critical need as robots increasingly operate in contested or untrusted settings.