Salman Khalid
Papers
5
Total Citations
64
H-Index
4
About
Salman Khalid is at the forefront of intelligent manufacturing, specializing in Prognostics and Health Management (PHM) and deep learning for industrial robotics. His research focuses on ensuring the reliability and longevity of critical robotic components, particularly rotating machinery like Rotate Vector (RV) and strain wave gear reducers. Khalid’s major contributions include pioneering deep learning approaches for fault diagnosis under nonstationary and variable working conditions, addressing the critical challenge of imbalanced data in real-world industrial settings. His comprehensive 2023 review on PHM for industrial robots, with 43 citations, has become a foundational reference in the field. He has also developed innovative transfer learning and area-metric-based sampling methods to enhance health monitoring accuracy. Beyond traditional robotics, Khalid explores novel actuation technologies, such as SMA-textile actuators for soft robotics and wearables, demonstrating his versatility. With a growing body of work that includes recent publications on smart factory health assessment, his research is shaping the future of autonomous, reliable, and intelligent manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5