Zahra Moezkarimi
Papers
2
Total Citations
8
H-Index
2
About
Zahra Moezkarimi is a theoretical computer scientist whose research centers on approximation algorithms for geometric optimization problems, with a particular focus on the freeze-tag problem (FTP) and its variants. Her major contributions lie in developing provably efficient solutions for multi-robot wake-up and coordination scenarios, where one mobile robot must awaken a team of sleeping robots in minimal time. In her 2015 work, she designed an O(1)-approximation algorithm for the 2-dimensional geometric freeze-tag problem, guaranteeing a constant-factor performance ratio—a significant theoretical milestone that provides a practical bound for real-world applications. Her 2014 paper further advanced the field by presenting a Polynomial-Time Approximation Scheme (PTAS) for the geometric 2-FTP, offering a tunable trade-off between solution quality and computational cost. Though her citation counts (4 each) reflect a focused, early-career impact, these contributions are foundational for researchers in robotics, swarm intelligence, and geometric optimization. Moezkarimi’s work demonstrates how elegant algorithmic theory can directly inform the design of efficient multi-agent systems, making her a promising voice in approximation algorithms.
Research Focus
Key Achievements
Top Papers
- 1
- 2A PTAS for geometric 2-FTP4 citations · 2014