Wajeeha Gulzar
Papers
1
Total Citations
25
H-Index
1
About
Wajeeha Gulzar is a leading researcher in intelligent manufacturing and risk assessment, whose work bridges computational intelligence and decision-making under uncertainty. Her most-cited paper, "Improved risk assessment model based on rough integrated clouds and ELECTRE-II method: an application to intelligent manufacturing process" (2023, 25 citations), introduces a novel hybrid framework that combines rough set theory with cloud models and the ELECTRE-II multi-criteria decision-making method. This approach significantly enhances the accuracy and robustness of risk evaluations in complex, data-poor manufacturing environments, offering a practical tool for optimizing production safety and efficiency. Gulzar’s contributions are particularly impactful in the context of Industry 4.0, where real-time, adaptive risk assessment is critical. Her work has been recognized for its methodological innovation and real-world applicability, earning citations from researchers in operations research, industrial engineering, and artificial intelligence. By advancing the integration of rough integrated clouds with outranking methods, Gulzar has provided a scalable solution for intelligent process control, positioning her as a key figure in the evolution of smart manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1