About

Shoujie Li is a robotics researcher whose work sits at the intersection of tactile sensing, intelligent grippers, and human-robot interaction. His research is primarily driven by a compelling challenge: enabling robots to perceive and manipulate objects reliably in environments where vision fails — whether underwater, in darkness, or amid smoke and reflections. His most influential contribution, "TaTa" (2022, 35 citations), introduced a universal jamming gripper combining large-area tactile sensing with high precision, demonstrating particular promise for underwater manipulation tasks. Building on this foundation, JamTac (2023) extended these capabilities with integrated sensing-grasping functionality for low-visibility environments. Li's more recent work has pushed into bio-inspired sensing, with a mechanoluminescent visuotactile sensor (2025, 27 citations) that mirrors biological event-driven perception for real-time intelligent interaction. His dual-modal electronic skin research further advances bidirectional human-robot interaction by coupling tactile perception with haptic feedback. Beyond sensing, Li has contributed to cable-driven robotic arm design, liquid manipulation, and safe reinforcement learning for unstructured environments. With over 110 cumulative citations, his body of work reflects a systematic effort to give robots the tactile intelligence necessary to operate meaningfully in complex, real-world conditions.

Research Focus

Key Achievements

6
H-Index
11
Papers
114
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
TaTa: A Universal Jamming Gripper with High-Quality Tactile Perception and Its Application to Underwater Manipulation
35 citations · 2022
📈 Most Prolific Year: 2025 (4 Papers)
🤝 Key Collaborators: 39
🏛 Institutions: Tsinghua–Berkeley Shenzhen Institute, University Town of Shenzhen, Colorado School of Mines, Tsinghua University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago