Qiqi Shu
Papers
1
Total Citations
5
H-Index
1
About
Qiqi Shu is a rising researcher at the forefront of augmented reality (AR) and human-computer interaction, with a primary focus on real-time localization and pose estimation. Their most cited work, "ARLO: Augmented Reality Localization Optimization for Real-Time Pose Estimation and Human–Computer Interaction" (2025), tackles the critical challenge of achieving accurate, outdoor AR localization. By analyzing and optimizing the visual-inertial odometry (VIO) and SLAM algorithms underpinning platforms like Apple’s ARKit, Shu has proposed novel methods to enhance robustness in dynamic, real-world environments. This contribution is vital for advancing applications in autonomous navigation, robotics, and seamless AR experiences. With 5 citations already in a short time, Shu’s work is gaining traction for its practical impact on bridging the gap between indoor and outdoor AR performance. Their research not only pushes the boundaries of spatial computing but also lays essential groundwork for more reliable, user-centric interactive systems. As a forward-thinking innovator, Qiqi Shu is poised to shape the next generation of immersive technology.
Research Focus
Key Achievements
Top Papers
- 1