Ayesha Maqbool

National University of Sciences and Technology

Papers

Total Citations

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About

Dr. Ayesha Maqbool’s research lies at the intersection of decision science, artificial intelligence, and software engineering, with a particular emphasis on fuzzy logic and multi-criteria group decision-making. Her most cited work introduces induced bipolar neutrosophic aggregation operators based on Einstein operations, a novel framework that enhances the handling of uncertainty and vagueness in complex decision environments. This contribution, published in 2023 and garnering 6 citations, provides a robust mathematical foundation for selecting optimal solutions—such as robotic systems—under conflicting criteria. In parallel, Dr. Maqbool has advanced software engineering by developing an intelligent platform for mining and retrieving reusable software components, addressing critical challenges in robotic, IoT, and sensor-based application development. Her work bridges theoretical innovation with practical tool-building, enabling more efficient and adaptive software ecosystems. With a growing citation footprint, Dr. Maqbool’s research is recognized for its clarity and applicability, offering students and practitioners actionable frameworks for tackling real-world problems in automation and intelligent systems. Her achievements reflect a commitment to both foundational theory and translational impact.