Yi-Shiuan Tung
Papers
3
Total Citations
16
H-Index
2
About
Yi-Shiuan Tung is a researcher advancing the frontier of human-robot collaboration (HRC) and intelligent manufacturing systems. Her work centers on making robots more perceptive, predictive, and legible partners for human workers. A key contribution is her development of workspace optimization techniques that significantly improve the prediction of human motion during collaborative tasks—a foundational challenge for safe interaction, as highlighted in her 2024 paper (9 citations). She also tackles complex logistical problems in manufacturing, introducing a bilevel optimization framework for just-in-time robotic kitting and delivery that adaptively segments tasks and schedules to boost efficiency (2022, 5 citations). Beyond prediction, Tung explores how robots can actively communicate their intentions to humans; her 2023 study (2 citations) demonstrates that combining augmented reality with workspace preparation enhances robot legibility, making collaborative sequences more intuitive. By addressing both the robot’s ability to anticipate human actions and its capacity to be understood, Tung’s research is shaping a future where human-robot teams operate with greater safety, trust, and fluidity.
Research Focus
Key Achievements
Top Papers
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