Nasreen Kausar
Papers
9
Total Citations
72
H-Index
6
About
Nasreen Kausar is a prolific researcher whose work sits at the dynamic intersection of fuzzy mathematics, neutrosophic set theory, and computational decision-making. Her primary contributions center on advancing multi-criteria and multi-attribute decision-making (MADM/MCDM) frameworks through the development of sophisticated fuzzy set extensions — including Fermatean vague normal sets, q-rung complex diophantine neutrosophic sets, and linear Diophantine fuzzy systems — applied to real-world challenges such as robotic sensor selection and medical engineering evaluation. A defining thread throughout Kausar's research is her commitment to addressing uncertainty and imprecision in complex systems. Her highly cited work on generalized fuzzy differential equations and numerical schemes for fuzzy linear and nonlinear systems demonstrates her versatility across both theoretical and applied mathematics, with relevance to classical mechanics, thermodynamics, and electrodynamics. Her aggregation operator frameworks and extended PROMETHEE methods have proven particularly impactful in engineering selection problems involving robotics. Collectively accumulating over 70 citations across recent publications, Kausar's work reflects a growing influence in computational intelligence and soft computing communities. Her research equips engineers and decision scientists with robust mathematical tools to model ambiguous, real-world environments with greater precision and reliability.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9