Muhammad Bilal Khan
Papers
2
Total Citations
14
H-Index
2
About
Muhammad Bilal Khan is an emerging researcher working at the intersection of fuzzy mathematics, decision-making theory, and intelligent systems. His scholarly contributions focus primarily on developing and applying advanced fuzzy set frameworks — including intuitionistic fuzzy rough sets and newly defined fuzzy set extensions — to solve complex real-world optimization and selection problems. Khan's most recognized work explores the application of sophisticated aggregation operators, particularly Yager-based operators, to multi-attribute decision-making (MADM) challenges. His 2023 paper on the robotic industry, which has garnered 12 citations, demonstrates how intuitionistic fuzzy rough Yager aggregation operators combined with the EDAS technique can effectively prioritize critical factors shaping the robotics sector — addressing the inherent challenges of vague and imprecise data in industrial analysis. His more recent 2025 contribution extends this expertise into agricultural technology, applying novel fuzzy set methodologies to guide the selection of agribots, highlighting his commitment to translating theoretical frameworks into practical, sector-specific solutions. Khan's research sits at a valuable crossroads of artificial intelligence, operations research, and engineering decision support. For students and researchers navigating uncertainty modeling and intelligent system design, his growing body of work offers rigorous mathematical tools with meaningful real-world applicability.
Research Focus
Key Achievements
Top Papers
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