Murat Ugur Gulle
Papers
2
Total Citations
229
H-Index
2
About
Dr. Murat Ugur Gulle is a leading researcher in computational optimization and artificial intelligence, with a primary focus on developing hybrid algorithms that synergize reinforcement learning with metaheuristic methods. His most cited work, "Hybrid algorithms based on combining reinforcement learning and metaheuristic methods to solve global optimization problems" (2021, 146 citations), introduces novel frameworks that enhance solution quality and convergence speed for complex, high-dimensional problems. Dr. Gulle has also made significant contributions to robotics and autonomous navigation through his "Adapted-RRT" approach (2021, 83 citations), which integrates sampling-based planning with metaheuristic optimization to efficiently solve three-dimensional path planning challenges. His research addresses critical gaps in global optimization and motion planning, offering practical solutions for engineering and AI applications. With over 200 combined citations, Dr. Gulle's work is recognized for bridging theoretical advances with real-world problem-solving, making him a notable figure in the fields of computational intelligence and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2