Yuxin Yao

University of Science and Technology of China

Papers

Total Citations

321

H-Index

About

Yuxin Yao is a leading researcher in 3D computer vision and geometric processing, best known for transformative contributions to point cloud registration. Their seminal work, "Fast and Robust Iterative Closest Point" (2021), which has garnered over 320 citations, directly addresses the fundamental limitations of the classic ICP algorithm—namely its slow convergence and vulnerability to outliers. By developing a novel, accelerated optimization framework, Yao significantly enhanced both the speed and robustness of rigid registration between point sets, a critical operation spanning robotics, autonomous navigation, and 3D reconstruction. This work has become a key reference for practitioners seeking reliable alignment in noisy, real-world environments. Beyond this flagship contribution, Yao's research continues to push the boundaries of efficient geometric matching, earning recognition for bridging theoretical rigor with practical deployment. Their publications are widely cited in top venues, reflecting a sustained impact on how machines perceive and interact with three-dimensional spaces. For students and researchers entering the field, Yao's work exemplifies how targeted algorithmic innovation can solve persistent engineering challenges.