Punsara Mahawela
Papers
1
Total Citations
2
H-Index
1
About
Punsara Mahawela is a researcher at the forefront of autonomous robotics and radar signal processing, with a focus on enhancing the perception capabilities of self-driving systems. His most-cited work, "Graph Neural Network Based 77 GHz MIMO Radar Array Processor for Autonomous Robotics" (2024), addresses a critical bottleneck in FMCW MIMO long-range radars: the trade-off between maximum range and beam scanning time. By introducing a graph neural network (GNN) processor, Mahawela’s approach enables transmit beamforming and beam scanning without sacrificing frame rate, effectively extending radar range while maintaining real-time performance. This innovation is pivotal for autonomous robotics, where reliable long-range detection is essential for safety and navigation. With 2 citations already, his work is gaining traction in the robotics and radar communities. Mahawela’s contributions bridge deep learning and hardware-aware signal processing, offering a scalable solution for next-generation autonomous systems. His research not only advances radar technology but also demonstrates the power of GNNs in tackling complex, real-world engineering challenges.
Research Focus
Key Achievements
Top Papers
- 1