Jingyu Shi
Papers
1
Total Citations
10
H-Index
1
About
Jingyu Shi is a rising researcher in computer vision and robotics, with a focus on understanding complex dynamic environments through object-object interactions. Their key contribution is the introduction of “Interacting Objects,” a pioneering dataset that captures rich, non-human interactions—such as those between tools, conveyors, and robotic arms in factories, surgical settings, and warehouses. This work addresses a critical gap in scene understanding, where most datasets emphasize human-object interactions, leaving machine-machine and object-object dynamics underexplored. Since its 2023 publication, the paper has garnered 10 citations, signaling growing interest from the robotics and embodied AI communities. Shi’s research paves the way for safer, more autonomous systems in industrial automation and collaborative robotics, enabling machines to reason about their surroundings beyond human presence. By cataloguing these nuanced interactions, they provide a foundational resource for richer dynamic scene representations. With this work, Jingyu Shi is establishing themselves as a key voice in advancing how robots perceive and act in complex, multi-agent environments—a critical step toward truly intelligent automation.
Research Focus
Key Achievements
Top Papers
- 1