Linkai Tao
Papers
1
Total Citations
6
H-Index
1
About
Dr. Linkai Tao is a rising innovator in the field of biosignal-based human-computer interaction (HCI), with a primary focus on electrooculography (EOG) signal processing and eye movement classification. His most notable contribution is the development of the **Residual Self-Calibrated Network with Multi-Scale Channel Attention**, a deep learning architecture that dramatically improves the accuracy of EOG-based eye movement classification. This work, published in 2024 and already garnering 6 citations, addresses a critical bottleneck in EOG-HCI technology—the fundamental step of accurately interpreting eye movements. By integrating residual learning with self-calibration and multi-scale attention mechanisms, Dr. Tao’s model enhances feature extraction from noisy biosignals, paving the way for more reliable assistive robots, augmented reality systems, and hands-free gaming interfaces. His research directly tackles the industrial demand for robust, real-time HCI solutions, positioning him as a key contributor to the next generation of accessible technology. With his work bridging advanced neural network design and practical biosignal applications, Dr. Tao is a researcher to watch in the evolving landscape of intelligent human-machine interaction.
Research Focus
Key Achievements
Top Papers
- 1