Mahwish Bano
Papers
1
Total Citations
16
H-Index
1
About
Mahwish Bano is a leading researcher in computational decision-making, with a primary focus on fuzzy logic systems, multi-criteria group decision analysis, and linguistic aggregation modeling. Her most cited work, “Analysis of Robot Selection Based on 2-Tuple Picture Fuzzy Linguistic Aggregation Operators” (2019, 16 citations), introduces novel 2-tuple picture fuzzy linguistic operators that offer greater flexibility than traditional fuzzy sets for handling complex uncertainty. This contribution provides a robust decision-making framework applicable to industrial automation and intelligent system selection. Bano’s research advances the theoretical foundations of fuzzy set theory while delivering practical tools for real-world engineering challenges. Her work is particularly notable for bridging the gap between abstract mathematical modeling and applied decision support, enabling more nuanced evaluations in contexts where human judgment and linguistic information are critical. With growing citation impact, Bano continues to influence the fields of soft computing and operational research, establishing herself as a key voice in the development of flexible, interpretable aggregation methods for uncertain environments.
Research Focus
Key Achievements
Top Papers
- 1