Fahimeh Ramezani
Papers
3
Total Citations
59
H-Index
2
About
Fahimeh Ramezani is a robotics and artificial intelligence researcher whose work centers on the theory and practice of multi-robot systems, with a particular focus on task allocation and coordination. Her most influential contribution, "Task Allocation Using a Team of Robots" (2022), has garnered 43 citations and stands as a comprehensive survey of multi-robot task allocation (MRTA), synthesizing a wide range of problem variants and solution approaches that span robotics, computer science, operational research, and artificial intelligence. This work has quickly become a valuable reference for researchers navigating the complex landscape of collaborative robotic systems. Complementing this survey, Ramezani has made rigorous theoretical contributions through her work on the computational complexity and approximability of MRTA problems, specifically examining the challenging ST-MR-IA setting — where single-task robots must be assigned to multi-robot tasks instantaneously. These studies provide essential algorithmic foundations for real-world applications such as search and rescue missions and autonomous area exploration. Through her combined focus on both breadth and depth — from broad literature synthesis to precise complexity analysis — Ramezani has established herself as a meaningful contributor to the growing field of autonomous multi-robot systems, offering tools and frameworks that directly inform the design of scalable robotic solutions.
Research Focus
Key Achievements
Top Papers
- 1Task Allocation Using a Team of Robots43 citations · 2022
- 2Multi-Robot Task Allocation -- Complexity and Approximation14 citations · 2021
- 3Multi-Robot Task Allocation-Complexity and Approximation2 citations · 2021