Min Young Chang
Papers
1
Total Citations
29
H-Index
1
About
Dr. Min Young Chang is a leading researcher in robotics and autonomous navigation, specializing in 3D perception and place recognition for complex environments. Her most notable contribution is the development of SpoxelNet, a pioneering deep learning framework that introduces spherical voxel-based place recognition for 3D point clouds in crowded indoor spaces. This work, which has garnered 29 citations, addresses a critical gap in robotics: enabling reliable localization and mapping in cluttered, human-populated environments where traditional methods often fail. By rethinking how point cloud data is structured and processed, Dr. Chang’s approach significantly improves the robustness of robot navigation systems, moving beyond the outdoor-focused solutions that dominate the field. Her research directly impacts the full autonomy of service robots, autonomous vehicles, and augmented reality systems operating in dense indoor settings. Through SpoxelNet, Dr. Chang has established herself as a key innovator in deep learning for 3D spatial understanding, providing a foundation for future work in safe and efficient robot navigation in real-world, crowded spaces.
Research Focus
Key Achievements
Top Papers
- 1