Papers
2
Total Citations
5
H-Index
2
About
Yun Lin’s research lies at the intersection of machine learning, wireless communication, and human-robot interaction, with a focus on enabling more intelligent and cooperative robotic systems. Her work addresses critical challenges in both robot-to-robot and human-robot coordination. In her 2019 study on machine learning in wireless connected robotics swarms (3 citations), Lin explored how modulation recognition—a key technical component for reliable communication—can be optimized by selecting the correct classifier, directly impacting the performance of robot swarms negotiating and transmitting data. Earlier, in her 2011 paper on intention-based coordination for human-robot cooperative search (2 citations), she developed a multi-agent search scheme that uses stochastic models of human activity to estimate state, enabling robots to recognize and adapt to human intentions during joint tasks. This work contributes to more natural and effective human-robot interaction, particularly in search scenarios. Though her citation counts are modest, Lin’s contributions are foundational to advancing the reliability and intuitiveness of robotic systems in collaborative environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2