Canada
• Designed physics-informed Explainable AI (XAI) models using SHAP and XGBoost to enhance renewable energy systems. • Applied Graph Neural Network (GNN) classifiers for material stability assessment, achieving over 90% accuracy. • Contributed to the rapid screening and discovery of high-performance materials for clean energy applications. • Collaborated with a leading research institute, Forschungszentrum Jülich, focusing on innovative energy technologies.
• Maintaining and analyzing of data using VMDeL platform written in PHP larval on Heroku • Python data visualization and data analysis of atomistic datasets as output by large-scale MD/statics simulations. • Responsible for research on new polyelectrolytes membranes based on MD Simulations
• Coordinated theory and simulation methodologies for ab initio modeling of Pt electrocatalysis in PEMFCs as well as fundamental structural and electronic studies of graphene and N-doped graphene as catalyst support for Pt nanoparticles.
• Software development contributor in dispatching a public version of HORTON software (https://theochem.github.io/horton/) • Spin chemical reactivity indicators for open shell systems • Investigation on the accuracy of Fukui function