S. Sureshkumar
Papers
1
Total Citations
2
H-Index
1
About
S. Sureshkumar is a leading researcher in robust edge autonomy, sensor fusion, and trustworthy artificial intelligence for autonomous systems. Their most influential work, "STARNet: Sensor Trustworthiness and Anomaly Recognition via Approximated Likelihood Regret for Robust Edge Autonomy" (2023), introduces a novel framework that addresses a critical challenge in autonomous robotics: detecting and mitigating sensor failures in complex, real-time environments. By leveraging approximated likelihood regret, STARNet enables autonomous systems—equipped with LiDAR, RADAR, and event cameras—to recognize anomalies and maintain operational integrity despite intricate sensor-environment interactions. This contribution has garnered attention for its practical implications in safety-critical applications, earning early citations and establishing Sureshkumar as a thought leader in resilient perception systems. Their work bridges the gap between theoretical sensor trustworthiness and deployable edge computing solutions, directly impacting the reliability of autonomous vehicles and robotics. With a growing citation record and a focus on real-world robustness, Sureshkumar continues to shape how machines perceive and adapt to unpredictable surroundings, making their research essential for students and engineers advancing next-generation autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1