Rohan Ghosh
Papers
5
Total Citations
32
H-Index
3
About
Rohan Ghosh is a researcher at the forefront of neuromorphic engineering, where he draws inspiration from biological neural systems to advance robotic sensing and control. His work primarily focuses on tactile sensing, neuromorphic vision, and bio-inspired robotics. Ghosh’s major contributions include developing a neuromorphic approach to tactile edge orientation estimation using spatiotemporal similarity (2020, 12 citations), which enables robots to perceive surface features with human-like precision. He also pioneered a neuromorphic method for tactile texture recognition (2018, 8 citations), addressing a critical need in prosthetics and unstructured environment exploration. In vision, Ghosh achieved real-time robot tracking and following with neuromorphic vision sensors (2016, 7 citations), formulating a leader-follower paradigm for dynamic motion segmentation. His notable work extends to neurally inspired robotic control for gait rehabilitation in hemiplegic stroke patients (2014, 3 citations), demonstrating the translational potential of his research. Additionally, he explored depth estimation and object recognition in dark environments using the ATIS sensor (2014, 2 citations), pushing the boundaries of autonomous navigation under low illumination. With a cumulative impact of over 30 citations, Ghosh’s innovative fusion of neuroscience and robotics continues to inspire new pathways in intelligent, adaptive machines.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Neuromorphic Approach to Tactile Texture Recognition8 citations · 2018
- 3Real-time robot tracking and following with neuromorphic vision sensor7 citations · 2016
- 4
- 5Depth estimation and object recognition in dark environments using ATIS2 citations · 2014