Michael J. McCourt

Papers

Total Citations

H-Index

About

Michael J. McCourt’s research lies at the intersection of control theory, networked systems, and human-autonomy interaction, with a focus on ensuring stability and security in complex, dynamic environments. His work addresses critical challenges in adversarial multi-agent systems and semi-autonomous control, where human operators intermittently intervene. In his 2017 paper on hybrid estimation for tracking adversarial teams, McCourt developed algorithms to model and predict the behavior of opposing networked agents—applicable to network security, economic decision-making, and robotic soccer. Though the paper has garnered 2 citations, its conceptual framework for adversarial reasoning is a foundational step in competitive multi-agent scenarios. His 2016 study on passive switched system analysis for semi-autonomous systems tackles the safety guarantees needed when human operators intermittently control autonomous platforms, such as drones or robots. By applying passivity theory to switched systems, McCourt provides rigorous stability conditions that ensure safe operation even during mode transitions. While his citation counts are modest, his contributions are notable for bridging theoretical control methods with real-world applications in security and human-robot collaboration, offering practical tools for engineers designing resilient, interactive autonomous systems.