Iman Mohamad Sharaf
Papers
4
Total Citations
44
H-Index
3
About
Iman Mohamad Sharaf’s research bridges the frontiers of fuzzy decision-making, robotics, and optimization, offering innovative solutions for complex industrial and computational challenges. His most impactful work introduces a **spherical fuzzy aggregation function** and a **spherical fuzzy EDAS** method, which revolutionized robot selection in manufacturing by handling uncertainty more effectively—earning 33 citations since 2022. Sharaf also pioneered a **novel ellipsoid algorithm** for robot selection, enhancing product quality and productivity in manufacturing environments, and developed an **exterior point algorithm** for linear complementarity problems, demonstrating versatility across theoretical and applied domains. His recent 2025 study on **trust and explainability in robotic hand control** integrates adversarial machine learning with EEG sensor data fusion, advancing human-robot interaction through fuzzy decision-making. With contributions spanning fuzzy logic, optimization, and robotics, Sharaf’s work has garnered growing recognition, including citations in top engineering journals. His ability to merge algorithmic rigor with real-world applications—from industrial automation to neuro-robotics—positions him as a key figure in intelligent systems research, inspiring students and researchers to explore the intersection of fuzzy mathematics and cutting-edge technology.
Research Focus
Key Achievements
Top Papers
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