Mohsen is a post-doctoral fellow at Polytechnique Montreal, collaborating with Maya HTT and Hydro-Quebec to develop digital twin models using Physics-Informed Neural Networks (PINNs). He completed his Ph.D. at Concordia University in January 2024, where he contributed to developing an in-house high-order unstructured flow solver in C++ based on the Flux Reconstruction (FR) approach. Additionally, he created a multi-layered parallel framework for aeroacoustics shape optimization using Python, integrating the gradient- free Mesh Adaptive Direct Search (MADS) algorithm and the Ffowcs Williams and Hawkings (FW-H) formulation for far-field noise. Mohsen also has over two years of industry experience as an aerodynamic and aeroacoustics specialist at Limosa Inc., wh ere he contributed to the design of an electric Vertical Take-Off and Landing (eVTOL) vehicle