Omar Barukab

Papers

Total Citations

100

H-Index

About

Omar Barukab is a leading researcher in computational intelligence and decision science, whose work bridges fuzzy logic systems and smart urban environments. His most influential contribution, "A New Approach to Fuzzy TOPSIS Method Based on Entropy Measure under Spherical Fuzzy Information" (2019, 94 citations), introduced a groundbreaking framework for handling multi-attribute group decision-making under uncertainty. By integrating entropy measures with spherical fuzzy sets (SFS)—one of the most powerful extensions of fuzzy set theory—Barukab developed a robust TOPSIS-based methodology that significantly improves how complex, ambiguous information is processed in real-world decisions. This work has become a cornerstone for researchers tackling uncertainty in engineering, management, and artificial intelligence. Beyond theoretical advances, Barukab explores the socio-technical challenges of smart cities. His 2021 study on "Intelligent Socio-Emotional Control of Pedestrian Crowd Behaviour inside Smart City" (6 citations) addresses the critical interplay between human emotions, social dynamics, and autonomous systems—robots, drones, and smart vehicles—in urban spaces. This research highlights the need for emotionally aware crowd management as cities become increasingly automated. Barukab’s dual focus on foundational fuzzy decision models and applied smart city intelligence marks him as a versatile scholar shaping both theory and practice in intelligent systems.