Hemant Kumawat
Papers
2
Total Citations
53
H-Index
2
About
Hemant Kumawat is a researcher specializing in autonomous systems, edge computing, and multi-modal sensor fusion, with a focus on developing resource-efficient solutions for real-time decision-making in robotics and autonomous vehicles. His work sits at the intersection of computer vision, embedded AI, and intelligent sensing architectures, addressing the critical challenge of balancing computational efficiency with task performance in resource-constrained environments. Kumawat's most cited contribution, "Task-Driven RGB-Lidar Fusion for Object Tracking in Resource-Efficient Autonomous Systems" (2021, 51 citations), demonstrates his innovative approach to selectively fusing Lidar and RGB sensor data, reducing unnecessary computational overhead while maintaining robust object tracking performance. This work has proven particularly impactful for the autonomous vehicles and robotics communities, where hardware limitations demand intelligent resource management. His more recent work, "Intelligent Sensing-to-Action for Robust Autonomy at the Edge" (2025), reflects his evolving research agenda toward closing the loop between perception and actuation in dynamic real-world environments, tackling emerging challenges in smart cities and edge robotics. Kumawat's research trajectory positions him as a promising voice in the growing field of efficient, adaptive autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2