Dr Xinchen Zhang

My Ph.D. was focused on the fundamental investigation of fluid and particle dynamics in particle-laden flows using high-fidelity numerical methods. It was completed in 2022 with a Dean's Commendation for Doctoral Thesis Excellence.

Since completion, my work has primarily focused on integrating machine learning (ML) into low-fidelity computational fluid dynamics (CFD) tools for multiphase flow solutions. This work involves training ML models based on the fluid and particle data and physical information obtained in high-fidelity simulations and applying the trained models to low-fidelity simulations to improve the accuracy and efficiency of low-fidelity CFD simulations in predicting multiphase flows in industrial-scale applications.