Presentation

I am currently a PhD student at Université Paris-Saclay / CentraleSupélec, where I began my doctoral studies in October 2025. I also work as a Teaching Assistant at Université Paris-Saclay / Polytech. My PhD research focuses on the optimization of fire protection under uncertainty and its impact on health, under the supervision of Sahar Hoteit (Université Paris-Saclay) and Jian Liu (University of Arizona). I received a Master’s degree in Applied Mathematics, Computational Finance, and Actuarial Science from « Université de Lille » in 2023.

PhD Context

Fire safety is a crucial aspect of building design and emergency response planning. The unpredictability of fire incidents due to variations in materials, environmental factors, and human responses necessitates the development of adaptive and optimized fire protection processes. Traditional fire protection systems rely on deterministic models, which often fail to accommodate real-world uncertainties. One of the primary drivers of increasing wildfire occurrences is climate change. Rising global temperatures lead to prolonged dry spells, creating an abundance of dry vegetation that fuels fires. Additionally, higher temperatures increase evaporation rates, reducing soil moisture and making forests more susceptible to ignition. Extreme weather events, such as heatwaves, strong winds, and lightning storms, further contribute to the spread and intensity of wildfires. The devastating Australian bushfires of 2019-2020 and the unprecedented California wildfires in recent years serve as stark reminders of the link between climate change and fire hazards. This project aims to address these challenges by incorporating probabilistic modeling, machine learning, and real-time monitoring into fire safety designs.

PhD Metholody

• Uncertainty Analysis in Fire Protection
  • Identification of key uncertainties in fire dynamics and human behavior.
  • Monte Carlo simulations and probabilistic risk assessments to model fire spread and response times.
• Optimization of Fire Safety Measures
  • Application of artificial intelligence and machine learning for predictive fire modeling.
  • Design of smart fire detection and suppression systems with real-time data analytics.
• Impact on Human Health
  • Assessment of health effects from prolonged exposure to fire-related pollutants.
  • Development of evacuation models that minimize exposure to harmful gases.
  • Evaluation of ventilation and filtration systems to reduce smoke inhalation.