Papers

3

Total Citations

29

H-Index

3

About

Suman Ghosh is a researcher working at the intersection of neuromorphic computing, computer vision, and robotics, with a particular focus on event-based sensing and 3D perception. His work explores how bio-inspired event cameras — novel sensors that detect asynchronous, per-pixel brightness changes with exceptional temporal resolution — can be harnessed to solve fundamental challenges in depth estimation, visual attention, and simultaneous localization and mapping (SLAM). Ghosh's most influential contribution, "Event-driven proto-object based saliency in 3D space" (2022, 14 citations), advances robotic visual attention by integrating depth cues with proto-object representations, enabling robots to meaningfully organize and prioritize their visual environment. His comprehensive survey on event-based stereo depth estimation (2025, 8 citations) has quickly become a key reference for researchers entering this rapidly evolving field, synthesizing the state of the art in a domain central to autonomous navigation. His work on ES-PTAM (2025, 7 citations) further demonstrates his commitment to translating event-camera theory into practical robotic systems through stereo parallel tracking and mapping. With a growing citation record and contributions spanning perception, attention, and 3D reconstruction, Ghosh represents an emerging voice shaping the future of neuromorphic vision in robotics.

Research Focus

Key Achievements

3
H-Index
3
Papers
29
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Event-driven proto-object based saliency in 3D space to attract a robot’s attention
14 citations · 2022
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Italian Institute of Technology, Technische Universität Berlin, Robotics Research (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago