Papers
1
Total Citations
3
H-Index
1
About
Guowei Han is a researcher at the forefront of computational sensing and intelligent interaction, with a primary focus on haptic perception and neural operator methods. His work bridges the gap between machine learning and physical sensing, particularly in the context of slender rod structures—a challenging domain where traditional sensing approaches often fall short. Han’s most notable contribution, the 2025 paper "Neural operator-based haptic sensing along slender rods," introduces a novel framework that leverages neural operators to infer contact forces and deformations along flexible, rod-like objects. This approach enables real-time, high-fidelity haptic feedback without the need for dense sensor arrays, offering transformative potential for applications in soft robotics, medical catheters, and virtual reality. Although early in its citation trajectory, the work has already garnered 3 citations, signaling growing interest from the robotics and sensing communities. Han’s research stands out for its elegant synthesis of operator learning and physical modeling, promising to redefine how machines perceive and interact with their environments through touch.
Research Focus
Key Achievements
Top Papers
- 1Neural operator-based haptic sensing along slender rods3 citations · 2025