Papers
1
Total Citations
2
H-Index
1
About
Zibo Qi is a leading researcher in nuclear fusion engineering and intelligent robotic systems, with a primary focus on the China Fusion Engineering Test Reactor (CFETR). His most notable contribution is the development of a transformer-enhanced Temporal Convolutional Network to compensate for control delays in the CFETR Multi-Purpose Overload Robot, a critical system for divertor maintenance in tokamak reactors. This work, published in 2025, addresses a key challenge in remote handling for fusion energy—ensuring precise, real-time robotic manipulation despite inherent communication and processing lags. By integrating temporal convolutional networks with transformer architectures, Qi’s approach significantly improves predictive accuracy and adaptive control, advancing the feasibility of autonomous maintenance in extreme environments. While his citation count is still growing, his research sits at the intersection of deep learning, robotics, and fusion energy, demonstrating a forward-looking methodology that balances theoretical innovation with practical engineering constraints. Qi’s work is particularly relevant for researchers in nuclear robotics and AI-driven control systems, offering a template for handling time-sensitive operations in high-stakes settings.
Research Focus
Key Achievements
Top Papers
- 1