Mohammad Moeini

WORK HISTORY

EDUCATION

ABOUT MOHAMMAD MOEINI

Leveraging expertise in Scientific Computing and High-Performance Computing (HPC), I am a dedicated engineer specializing in Catastrophe Modeling & Simulation, and C++/CUDA programming.Currently at Penn State Institute for Computational and Data Sciences, I enhance scientific workflows, benchmark scientific tools such as STAR-CCM+ and OpenFOAM, and provide comprehensive solutions for parallelization and optimizing scientific computing tasks.Notably, my experience extends to applying Machine Learning techniques in Computational Fluid Dynamics (CFD) and using sophisticated tools like Python, BASH, and scikit-learn. I secured research funding for this work and notably improved the accuracy of SOTA models for hurricane surge and wave load estimation.Earlier in my career, I honed my skills in Nonlinear Finite Element Analysis (FEA), macromodeling, and structural damage analysis post-disaster, using tools such as ABAQUS FEA and OpenSEES.My comprehensive suite of skills includes CUDA C++, Python, Design of Experiments (DoE), Gaussian Mixture Models (GMM), Ensemble Learning and Dynamic Time Warping (DTW) modeling techniques. These skills, combined with my demonstrated ability to lead research projects and secure funding, make me a versatile Scientific Computing Engineer.I am always eager to embrace new challenges and bring my problem-solving skills, team collaboration, and dedication to high-impact research roles. I continually aim to push the frontiers of computational science to deliver game-changing insights that shape decision-making and create robust value for stakeholders.