E-Learning
Certificates live in Documents. Below are the skills I actively use.
Introduction to High-Throughput Materials Development · Georgia Tech · Nov 2024 · completed
- Takeaway: HT library design, high-throughput characterization & property screening; PSP linkages and MGI-style workflows.
- Applied in: Feature planning + workflow design across projects (see Projects).
Materials Data Sciences & Informatics · Georgia Tech · Sep 2024 · completed
- Takeaway: Materials informatics, 2-point statistics & PCA for structure, homogenization, and cyberinfrastructure for data integration.
- Applied in: Feature engineering & explanations for formation-energy / melting-point models (see Projects).
Density Functional Theory · École Polytechnique · Oct 2025 · completed
- Takeaway: Foundation (mathematical and historical) of DFT, approximation strategies, Quality and accuracy of different approximations, practical procedure to solve the equations, Ready to be operative and use DFT.
- Applied in: To understand, to evaluate the quality and to use DFT datasets (e.g., Materials Project, OQMD etc.), to verify randomly generated materials' property in a current project
Machine Learning Specialization · DeepLearning.AI/Stanford · April 2023 · completed
- Takeaway: Supervised ML, trees/ensembles, unsupervised & recommenders, plus ML best practices.
- Applied in: Stacking for melting-point prediction and ensemble voting for oxidation-state assignment.
Generative AI for Data Scientists Specialization · IBM · Dec 2024 · completed
- Takeaway: Prompt engineering and hands-on GenAI for data augmentation, feature ideas, and model refinement.
- Applied in: Semantic band-gap knowledge graph & LLM-assisted retrieval (see Projects).
FEM — Linear, Nonlinear Analysis & Post-Processing · Coursera Project Network · May 2025 · completed
- Takeaway: Set up linear/nonlinear static analyses, cloud simulation, and post-processing for validation.
- Applied in: Sensor modeling (Masters) and 2D elasticity work; complements COMSOL/Abaqus skills.