Lior Rokach
Papers
3
Total Citations
65
H-Index
3
About
Lior Rokach is a leading researcher in autonomous systems, with a primary focus on enhancing the reliability and safety of robotic platforms through advanced fault detection and diagnosis. His work addresses a critical challenge in robotics: ensuring that autonomous agents can identify and respond to sensor failures in real-time, preventing catastrophic task failures. In his highly cited 2013 paper, "Sensor fault detection and diagnosis for autonomous systems" (29 citations), Rokach established foundational methods for interpreting sensor data to detect anomalies. He further advanced the field with a hybrid approach in 2017 (24 citations), which improved unsupervised fault detection by tackling the problem of unclassified data—where most datasets lack clear labels for normal or faulty states. This innovation is particularly impactful for real-world applications where labeled training data is scarce. Rokach’s contributions have significantly improved the robustness of autonomous physical agents, from drones to industrial robots, making them more dependable in unpredictable environments. His work is essential reading for students and engineers developing resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Sensor fault detection and diagnosis for autonomous systems29 citations · 2013
- 2
- 3A hybrid approach for fault detection in autonomous physical agents12 citations · 2014