Joyce Jiyoung Whang
Papers
1
Total Citations
23
H-Index
1
About
Joyce Jiyoung Whang is a leading researcher at the intersection of graph representation learning and robotic manipulation. Her work fundamentally advances how robots understand and interact with objects by integrating structured knowledge with physical action. In her highly influential paper, "Semantic Grasping Via a Knowledge Graph of Robotic Manipulation," Whang pioneers a graph-based approach that enables robots to reason not just about where to grasp an object, but which gripper to use for a given task—a critical step toward truly intelligent, task-aware manipulation. This contribution, which has already garnered 23 citations, addresses a key limitation in prior semantic grasping models that focused solely on object affordances. By embedding robotic manipulation knowledge into a graph structure, Whang’s work bridges the gap between symbolic reasoning and physical robotics, offering a scalable framework for more adaptive and context-sensitive robotic systems. Her research is poised to shape the future of autonomous grasping, making robots more capable in unstructured environments like homes and warehouses.
Research Focus
Key Achievements
Top Papers
- 1