Samuel Bello

Johns Hopkins University

Papers

1

Total Citations

3

H-Index

1

About

Dr. Samuel Bello is pioneering the field of neuromorphic tactile sensing, with a focus on creating artificial touch systems that rival human dexterity. His key research areas include biomimetic tactile processing, spiking neural networks for sensory data, and robust texture classification for robotics and prosthetics. In his most cited work, "Invariant Neuromorphic Representations of Tactile Stimuli Improve Robustness of a Real‐Time Texture Classification System" (2025, 3 citations), Dr. Bello developed algorithms that transform raw tactile signals into neuron-like spiking representations. Crucially, these representations remain invariant to variations in scanning speed and contact force—two major obstacles in real-world tactile sensing. This breakthrough enables robots and prosthetic hands to reliably identify textures in dynamic, uncontrolled environments, a significant step toward restoring natural touch for amputees. While early in his career, his work has already garnered attention for its potential to bridge the gap between biological and artificial touch. Dr. Bello’s contributions are laying the groundwork for more intuitive human-machine interaction, promising to enhance the autonomy and sensory feedback of next-generation robotic and assistive technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Invariant Neuromorphic Representations of Tactile Stimuli Improve Robustness of a Real‐Time Texture Classification System
3 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Johns Hopkins University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago