Papers
3
Total Citations
17
H-Index
2
About
Luis Burbano is a researcher at the forefront of secure and resilient control systems, with a primary focus on cyber-physical systems (CPS) and multi-agent coordination. His work addresses the critical challenge of safeguarding autonomous systems—from industrial control networks to multi-robot teams—against malicious cyber-attacks. Burbano’s major contributions include developing practical strategies for attack detection and mitigation, as demonstrated in his most-cited work, "Dynamic Data Integration for Resilience to Sensor Attacks in Multi-Agent Systems" (2021, 11 citations), which proposes a real-time data fusion method to maintain system integrity under sensor compromise. He has also advanced distributed control theory, notably through "Distributed MPC and Potential Game Controller for Consensus in Multiple Differential-Drive Robots" (2019, 4 citations), which combines model predictive control with game-theoretic principles to achieve efficient consensus among robots with limited computational resources. His most recent work, "Fast Attack Recovery for Stochastic Cyber-Physical Systems" (2024, 2 citations), tackles the urgent need for rapid restoration of CPS functionality after security breaches. Burbano’s research is pivotal for building trust in next-generation autonomous systems, and his growing citation record reflects the increasing relevance of his contributions to both academia and industry.
Research Focus
Key Achievements
Top Papers
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- 2
- 3Fast Attack Recovery for Stochastic Cyber-Physical Systems2 citations · 2024