Pahan Mendis
Papers
1
Total Citations
2
H-Index
1
About
Dr. Pahan Mendis is a rising researcher at the intersection of autonomous robotics, radar signal processing, and deep learning. His work focuses on enhancing the perception capabilities of autonomous systems, particularly through the integration of graph neural networks (GNNs) with millimeter-wave radar technology. In his most cited work, "Graph Neural Network Based 77 GHz MIMO Radar Array Processor for Autonomous Robotics" (2024, 2 citations), Mendis addresses a critical limitation of FMCW MIMO long-range radars: their restricted maximum range. He proposes a novel approach using transmit beamforming and beam scanning to extend range, while mitigating the associated increase in scanning time through intelligent GNN-based processing. This contribution is significant for enabling more reliable and longer-range sensing in autonomous robots. Though early in his career, Mendis is already demonstrating a talent for combining hardware-aware radar design with advanced machine learning architectures. His research holds promise for advancing the state of the art in autonomous navigation, particularly in safety-critical applications where robust, long-range perception is essential.
Research Focus
Key Achievements
Top Papers
- 1