Haseeb Ahmed Khan

National University of Sciences and Technology

Papers

Total Citations

H-Index

About

Haseeb Ahmed Khan is a rising researcher in the field of industrial automation and intelligent fault diagnostics, with a primary focus on hydraulic machinery and AI-driven condition monitoring. His most-cited work, "Fault Classification for Cooling System of Hydraulic Machinery Using AI" (2023, 8 citations), addresses a critical challenge in modern manufacturing and port operations: the reliable detection of faults in hydraulic cooling systems. By applying artificial intelligence to classify system anomalies, Khan’s research directly supports the growing demand for predictive maintenance in industries that rely on hydraulic equipment—such as mills, robotics, and heavy machinery—offering a pathway to reduce downtime and operational costs. His contributions are particularly notable for bridging the gap between traditional mechanical engineering and emerging AI technologies, making complex fault analysis more accessible and automated. While still early in his career, Khan’s work demonstrates significant potential to improve safety and efficiency in industrial settings, and his growing citation count reflects a timely and impactful contribution to the field of intelligent manufacturing systems.