Monji Zaidi
Papers
1
Total Citations
2
H-Index
1
About
Dr. Monji Zaidi is an emerging researcher whose work centers on the development and application of novel metaheuristic optimization algorithms, with a particular focus on the Golden Jackal Optimization (GJO) technique. His most notable contribution, the comprehensive survey titled "A comprehensive survey of golden jacal optimization and its applications" (2025), has already garnered 2 citations, establishing a foundational reference for scholars exploring nature-inspired computational methods. Dr. Zaidi’s research systematically maps the theoretical underpinnings, algorithmic variants, and diverse real-world applications of GJO—from engineering design to machine learning parameter tuning—demonstrating its potential as a robust alternative to established optimizers like particle swarm or genetic algorithms. His work is particularly significant for students and researchers seeking accessible, state-of-the-art reviews that bridge algorithmic theory and practical implementation. As an early-career scientist, Dr. Zaidi’s contributions are shaping the next generation of optimization research, offering clear pathways for innovation in complex problem-solving. His growing citation impact underscores the relevance of his surveys in guiding both novice and experienced researchers toward efficient, nature-inspired solutions.
Research Focus
Key Achievements
Top Papers
- 1A comprehensive survey of golden jacal optimization and its applications2 citations · 2025