Zhaohui Geng

The University of Texas Rio Grande Valley

Papers

Total Citations

H-Index

About

Zhaohui Geng is a researcher whose work centers on 3D point cloud registration, a foundational problem in robotics, computer vision, and automated manufacturing. His most-cited paper, "Minimax Registration for Point Cloud Alignment" (2022), introduces a robust framework for rigid registration that addresses the challenges of noise and outliers in high-precision 3D scanning. By formulating the alignment problem as a minimax optimization, Geng’s approach enhances accuracy and reliability in real-world applications—from industrial inspection to autonomous navigation. Though early in his citation trajectory, this work has already garnered attention for its theoretical clarity and practical utility, signaling growing impact in the field. Geng’s contributions are particularly relevant as manufacturing and robotics increasingly rely on automated 3D sensing. His research bridges the gap between algorithmic rigor and deployment-ready solutions, making him a promising voice in geometric data processing. For students and researchers exploring registration techniques, Geng’s work offers a compelling blend of mathematical depth and applied insight.