Shi-Li Zhang

Uppsala University

Papers

1

Total Citations

87

H-Index

1

About

Shi-Li Zhang is a pioneering researcher at the intersection of neuromorphic engineering and tactile sensing, whose work is redefining how electronic systems perceive and process touch. His most-cited paper, “Spike timing–based coding in neuromimetic tactile system enables dynamic object classification” (2024, 87 citations), introduces a paradigm-shifting approach that mimics the human somatosensory system’s ability to encode temporal information through precise spike timing. This breakthrough overcomes the limitations of conventional electronic skins, which rely on frame-based processing and struggle with dynamic tactile events. Zhang’s major contributions lie in developing bio-inspired coding strategies that enable rapid, efficient object classification during active touch—a critical capability for dexterous robotic manipulation and advanced prosthetics. His work bridges neuroscience and materials engineering, demonstrating how spike-timing-dependent plasticity can be harnessed for real-world haptic applications. With growing impact evidenced by recent citations, Zhang is establishing himself as a leading voice in neuromimetic systems, offering a compelling vision for next-generation tactile interfaces that learn and adapt like biological skin.

Research Focus

Key Achievements

1
H-Index
1
Papers
87
Total Citations
87
Avg Citations/Paper
🏆 Most Cited Paper
Spike timing–based coding in neuromimetic tactile system enables dynamic object classification
87 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Uppsala University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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