Shahanaz Ayub
Papers
2
Total Citations
29
H-Index
2
About
Shahanaz Ayub is a leading researcher in multi-robotic systems and intelligent navigation, whose work sits at the intersection of artificial intelligence and bio-inspired optimization. Her primary contributions focus on developing hybrid frameworks that integrate neural networks, fuzzy logic, and nature-inspired algorithms to solve the complex challenge of multi-robot path planning in dynamic environments. Her most influential work, a 2022 study on hybrid navigation methodologies, has garnered 22 citations, demonstrating its significant impact on the field. This research addresses a critical bottleneck in robotics: enabling multiple autonomous agents to navigate variable terrains efficiently and safely without collision. Ayub’s approach is notable for its practical synthesis of soft computing techniques, moving beyond theoretical models to implementable systems for industrial automation. Her 2021 companion paper, with 7 citations, further refines these methodologies, establishing her as a key voice in advancing swarm robotics and autonomous navigation. By bridging the gap between classical control and modern AI, Ayub’s work offers a scalable blueprint for the next generation of intelligent, collaborative robots.
Research Focus
Key Achievements
Top Papers
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