Papers
1
Total Citations
18
H-Index
1
About
Na Lei is a leading researcher at the intersection of computational geometry, differential geometry, and robotics, with a particular focus on surface parameterization and optimal transport. Her most influential work addresses the classical robotics challenge of **robot coverage path planning**, where she introduced an elegant geometric framework using quadratic differentials to compute efficient, nearly complete coverage paths for general surfaces. This approach minimizes duplicated area and has become a foundational method in the field, as evidenced by her highly cited 2017 paper on the topic (18 citations). Beyond coverage planning, Lei has made significant contributions to **conformal mapping** and **surface registration**, developing algorithms that enable robust shape analysis and texture mapping for complex 3D models. Her work bridges pure mathematics and practical engineering, offering rigorous solutions to problems in computer graphics, medical imaging, and autonomous navigation. With a growing citation record and a reputation for translating deep geometric theory into deployable algorithms, Na Lei continues to shape how robots perceive and navigate their environments, making her a key figure in modern computational geometry and robotics.
Research Focus
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Top Papers
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