Monica Ruiz-Martinez
Papers
1
Total Citations
4
H-Index
1
About
Monica Ruiz-Martinez is a researcher specializing in computational simulation and pathfinding algorithms, with a particular focus on emergency response scenarios. Her work bridges the gap between artificial intelligence and safety engineering, exploring how algorithmic efficiency can enhance real-world decision-making under crisis conditions. In her most cited paper, "Algorithm Comparison between A* and PRM on Indoor Fire Simulation," she systematically evaluates the performance of two prominent pathfinding algorithms—A* and Probabilistic Roadmap (PRM)—within simulated indoor fire environments. This study, which has garnered 4 citations, highlights the growing importance of cost-effective, low-risk simulation tools for training and planning in hazardous situations. By demonstrating the trade-offs between computational cost and navigational accuracy, Ruiz-Martinez contributes valuable insights for developing more reliable evacuation strategies and emergency response systems. Her work underscores the potential of simulation-based research to improve safety protocols without exposing individuals to real-world dangers, making her a notable voice in the intersection of robotics, artificial intelligence, and disaster management.
Research Focus
Key Achievements
Top Papers
- 1Algorithm Comparison between A* and PRM on Indoor Fire Simulation4 citations · 2020