Navneet Bhasin
Papers
1
Total Citations
6
H-Index
1
About
Dr. Navneet Bhasin is a leading researcher in autonomous systems and deep learning, with a primary focus on end-to-end learning for self-driving vehicles. His most cited work, "Autonomous Navigation via Deep Imitation and Transfer Learning: A Comparative Study" (2020, 6 citations), addresses a critical challenge in the field: developing robust deep neural networks (DNNs) that can replace the entire traditional driving pipeline. Bhasin’s research systematically compares imitation learning and transfer learning techniques, demonstrating how DNNs can learn complex driving behaviors directly from visual inputs. This work is foundational for reducing the data and training requirements of autonomous navigation systems, making them more scalable and adaptable to new environments. By tackling the "Achilles' heel" of DNN-based driving—the need for vast, diverse training datasets—Bhasin has contributed to more efficient and generalizable autonomous agents. His comparative analysis provides a clear roadmap for researchers and engineers seeking to deploy deep learning in real-world navigation tasks, bridging the gap between simulation and physical deployment.
Research Focus
Key Achievements
Top Papers
- 1