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About

Matthew J. Anderson is a leading researcher in autonomous robotics and cyber-physical systems, with a focus on enabling resilient operation in extreme and contested environments. His most impactful work centers on the DARPA Subterranean Challenge, where he was a key member of TEAM CoSTAR. Their seminal paper, "NeBula: Quest for Robotic Autonomy in Challenging Environments" (2021, 105 citations), details the novel algorithms, hardware, and software architecture that allowed robots to autonomously navigate and explore complex, GPS-denied tunnels and urban underground settings. This work has become a cornerstone for field robotics, demonstrating unprecedented levels of autonomy in unstructured, hazardous spaces. Beyond subterranean exploration, Anderson has contributed to perception with the "Caltech Aerial RGB-Thermal Dataset in the Wild" (2024) and to system security with "Fast Attack Recovery for Stochastic Cyber-Physical Systems" (2024), addressing vulnerabilities in safety-critical domains like autonomous driving. His research bridges the gap between robust autonomy and system resilience, making him a notable figure in advancing robots that can operate reliably when it matters most.