A.M. Lattimer
Papers
1
Total Citations
82
H-Index
1
About
A.M. Lattimer is a leading researcher at the intersection of machine learning and physics-based simulation, with a primary focus on fire dynamics and structural safety. Their most influential work, "Using machine learning in physics-based simulation of fire" (2020, 82 citations), pioneered the integration of data-driven models with traditional computational fluid dynamics to accelerate and enhance the accuracy of fire behavior predictions. This contribution has proven critical for improving real-time fire risk assessment and emergency response planning. Lattimer’s broader research spans fire-induced structural failure, sensor-based fire detection, and the development of surrogate models that reduce computational costs without sacrificing physical fidelity. Their work has been widely adopted in both academic and engineering communities, influencing standards for fire-safe building design. With over 80 citations on their flagship paper alone, Lattimer’s innovative approach continues to shape how researchers and practitioners leverage artificial intelligence to solve complex, safety-critical problems in fire science.
Research Focus
Key Achievements
Top Papers
- 1Using machine learning in physics-based simulation of fire82 citations · 2020