Papers
12
Total Citations
194
H-Index
10
About
Ya-Yen Tsai is a leading researcher in robotic manipulation, reinforcement learning, and tactile sensing, with a focus on bridging the sim-to-real gap for dexterous tasks. Her work has garnered over 185 citations, reflecting its impact on the field. Tsai’s major contributions include developing DROID, a framework that minimizes the reality gap using single-shot human demonstrations, and TacGNN, a hierarchical graph neural network enabling tactile-based in-hand manipulation without visual input—a breakthrough for blind robotic systems. She has also advanced tactile servoing for grasping adjustment under partial observation and egocentric human trajectory forecasting using wearable cameras, with applications for visually impaired assistance. Notably, her research on sim-to-real transfer for robotic manipulation with tactile sensory has been cited 27 times, underscoring its influence. Tsai’s achievements include pioneering constrained-space optimization and reinforcement learning for complex tasks, and designing a reconfigurable multirobot workcell for personalized manufacturing. Her work consistently integrates tactile feedback, virtual reality, and multi-modal fusion, pushing boundaries in contact-rich manipulation and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1DROID: Minimizing the Reality Gap Using Single-Shot Human Demonstration29 citations · 2021
- 2Sim-to-Real Transfer for Robotic Manipulation with Tactile Sensory27 citations · 2021
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- 6Constrained-Space Optimization and Reinforcement Learning for Complex Tasks17 citations · 2020
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