Xuelei Li

Papers

Total Citations

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About

Dr. Xuelei Li is a researcher at the intersection of cybersecurity and mobile robotics, with a primary focus on developing robust defenses against document-based cyberattacks in autonomous systems. His most notable contribution is the introduction of MMPD (Malicious Mobile PDF Detector), a novel framework designed to protect mobile robots from PDF-borne threats. Recognizing that PDFs are a common cross-platform document format—often embedded with malicious JavaScript or URIs—Li’s work addresses a critical vulnerability in human-robot interaction environments. The MMPD system, detailed in his 2020 paper, has garnered 8 citations and represents a pioneering step toward securing robotic platforms against file-based exploits. This research is particularly significant as robots increasingly share documents with humans in industrial and service settings. Li’s work bridges the gap between traditional cybersecurity and emerging robotic safety challenges, offering practical detection mechanisms that can be integrated into real-world robotic systems. By highlighting the unique attack surface presented by mobile robots, Dr. Li has laid important groundwork for future research in secure autonomous systems.