Ruixing Jia
Papers
4
Total Citations
58
H-Index
4
About
Ruixing Jia’s research lies at the intersection of robotic manipulation, multimodal perception, and human-robot interaction, with a focus on enabling robots to understand and interact with the physical world through touch, vision, and motion. A key contribution is the development of non-visual classifiers for granular materials, using force-feedback signals to identify material properties in visually constrained environments—a breakthrough for manipulation in low-visibility settings. Jia also pioneered deep visuo-tactile models for real-time liquid volume estimation during grasping, fusing raw RGB inputs with tactile sensor data to estimate liquid levels in deformable containers without extra calibration. In human-robot collaboration, Jia’s work on predicting human manipulation of large objects from full-body motions advances intention understanding, while research on learning autonomous viewpoint adjustment from human demonstrations improves telemanipulation by decoupling camera views from robot arm motion. With over 50 citations across these highly cited works, Jia’s contributions are shaping robust, perception-driven robotic systems capable of handling complex, real-world tasks—from granular material sorting to liquid handling and intuitive remote control.
Research Focus
Key Achievements
Top Papers
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- 3Visual-tactile Sensing for Real-time Liquid Volume Estimation in Grasping10 citations · 2022
- 4