Yara A. Jimnez-Nieto
Papers
1
Total Citations
4
H-Index
1
About
Yara A. Jiménez-Nieto is a researcher focused on computational simulation and pathfinding algorithms, with a particular emphasis on safety-critical applications. Her work bridges artificial intelligence and emergency response, as demonstrated in her most-cited paper, "Algorithm Comparison between A* and PRM on Indoor Fire Simulation" (2020, 4 citations). This study evaluates the performance of two prominent pathfinding algorithms—A* and Probabilistic Roadmap (PRM)—in simulated indoor fire scenarios, highlighting the growing importance of cost-effective, low-risk simulators for training and analysis. By comparing these algorithms, Jiménez-Nieto contributes to optimizing evacuation routes and improving safety protocols in hazardous environments. Her research underscores the value of simulation as a tool for reducing real-world risks, offering insights that can inform emergency planning and robotics. While her citation count is modest, her work addresses a critical niche in computational safety, making her a promising voice in the field of algorithm-driven simulation for disaster response.
Research Focus
Key Achievements
Top Papers
- 1Algorithm Comparison between A* and PRM on Indoor Fire Simulation4 citations · 2020