Pavanesh Narayanan
Papers
1
Total Citations
15
H-Index
1
About
Pavanesh Narayanan is a researcher at the forefront of autonomous driving perception, specializing in multimodal fusion and robust 3D object detection under adverse conditions. His most cited work, "SAMFusion: Sensor-Adaptive Multimodal Fusion for 3D Object Detection in Adverse Weather" (2024), introduces a novel framework that dynamically adapts sensor fusion strategies—integrating LiDAR, camera, and radar data—to maintain detection accuracy in fog, rain, and snow. This contribution directly addresses a critical bottleneck in real-world autonomous systems, where traditional fusion methods fail. With 15 citations in under a year, the paper has already influenced subsequent research in weather-robust perception. Narayanan’s work is notable for its practical emphasis on sensor-adaptive architectures, bridging the gap between theoretical fusion models and deployment in challenging environments. His research is essential reading for students and engineers working on safe autonomous navigation, offering a clear path toward more resilient perception systems.
Research Focus
Key Achievements
Top Papers
- 1