Niraj Bhujel
Papers
2
Total Citations
16
H-Index
2
About
Niraj Bhujel is a researcher at the forefront of autonomous navigation and human-robot interaction, specializing in deep reinforcement learning (DRL) and graph-based modeling for crowded environments. His work addresses the critical challenge of enabling mobile robots to safely and efficiently navigate among pedestrians by learning complex social dynamics. Bhujel’s major contributions include developing a Gated Graph Convolutional Network (GCN) framework that allows robots to identify and prioritize influential neighbors during DRL-based navigation, significantly improving policy learning in dense crowds. He has also advanced pedestrian trajectory prediction by disentangling intricate crowd interactions through graph structures, enabling more accurate forecasting of future paths. Both of his highly cited papers, published in 2023, have each garnered 8 citations, reflecting their immediate impact on the robotics and autonomous systems community. By integrating attention mechanisms with DRL, Bhujel’s work provides a principled approach to understanding relational dynamics in crowds, offering a foundation for safer, more socially-aware autonomous systems. His research is essential reading for students and engineers working on mobile robot navigation, multi-agent systems, and human-aware AI.
Research Focus
Key Achievements
Top Papers
- 1
- 2Disentangling Crowd Interactions for Pedestrians Trajectory Prediction8 citations · 2023