Marouane Bouadi is an Associate Professor at the School of Automotive and Transportation Engineering, Hefei University of Technology. In 2018, he received his PhD degree from Mohammed V University in Rabat, Morocco, specializing in Computational Physics - Physics of traffic flow. In 2019, he carried out postdoctoral research at the School of Transportation, Beijing Jiaotong University.

Marouane Bouadi's main research directions include: traffic modeling based on macroscopic models, microscopic car-following models, and machine learning models; studying the stability of mixed traffic flow with human-driven and automated-driven vehicles; and designing control strategies for automated-driven vehicles to alleviate / mitigate traffic congestion. Relevant research results have been published in several leading international journals, including Transportation Research Part B, Transportation Research Part C, and IEEE Transactions on Intelligent Transportation Systems.

Currently, Marouane Bouadi is the principal investigator of a project funded by the NSFC. The main objectives are: constructing theoretical models for human-driven vehicles that adequately consider stochastic factors, using methods such as machine learning to analyze the dynamics of human-driven vehicles and uncover the probabilistic nature of traffic jams; analyzing the stability of human-driven and automated-driven vehicles using stability analysis methods like the characteristic polynomial method, Laplace transformation, and Lyapunov method; and deducing optimal models for automated-driven vehicles that can improve traffic flow stability.

Languages for communication: Chinese (level 4), English, French, and Arabic.

Graduate students are welcome to apply.