Matthew Cavorsi
Papers
9
Total Citations
96
H-Index
4
About
Matthew Cavorsi is a robotics and cybersecurity researcher whose work sits at the intersection of multi-robot systems, adversarial resilience, and network security. His research focuses on developing algorithms and frameworks that enable robot teams to detect, isolate, and operate reliably in the presence of malicious or compromised agents — a critical challenge as autonomous systems become more prevalent in real-world environments. Cavorsi's most influential contribution, "Crowd Vetting" (2021, 29 citations), introduced a collaborative neighbor-based approach for identifying adversarial robots during Sybil attacks, demonstrating that robots can achieve high-probability malicious agent detection by leveraging local trust networks. Building on this, his work on Control Barrier Functions for adversarial resilience (2023, 26 citations) established rigorous mathematical guarantees for resilient multi-robot path planning and formation control under attack. His resilient hypothesis testing framework (2023, 14 citations) further extended these ideas into crowdsensing contexts, enabling robust group decision-making even when internal agents are compromised. Across his growing body of work, Cavorsi consistently addresses dynamic, real-world challenges such as shifting communication topologies and adaptive adversaries. With over 90 cumulative citations, his research offers foundational tools for engineers designing trustworthy, fault-tolerant autonomous robot networks.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multirobot Adversarial Resilience Using Control Barrier Functions26 citations · 2023
- 3Multi-Robot Adversarial Resilience using Control Barrier Functions15 citations · 2022
- 4Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots14 citations · 2023
- 5
- 6Exploiting Trust for Resilient Hypothesis Testing With Malicious Robots3 citations · 2024
- 7Providing Local Resilience to Vulnerable Areas in Robotic Networks2 citations · 2022
- 8Adaptive Malicious Robot Detection in Dynamic Topologies2 citations · 2022
- 9