I specialize in building intelligent, data-driven solutions that bridge the gap between Model-Based Systems Engineering (MBSE), Deep Learning, and Economic Analysis. My work focuses on automating complex engineering workflows and uncovering insights through spatial and statistical modeling.
| Project | Description | Tech Stack |
|---|---|---|
| π AI4SE IRS Generator | Automated generation of DoD-compliant IRS documents from Capella MBSE models using Google Gemini. | |
| π« CheXpert Classifier | Multi-label deep learning classifier for detecting chest X-ray pathologies with Grad-CAM explainability. | |
| π FEMA Aid Equity | Spatial and statistical analysis of disaster aid distribution in Puerto Rico using weighted vulnerability models. | |
| β‘ Green Hydrogen Model | Techno-economic LCOH comparison between KSA and USA featuring Monte Carlo uncertainty analysis. | |
| π DC Metro Analysis | Statistical study of COVID-19 and weather impacts on WMATA ridership using R and Tidyverse. | |
| π Explore More | Check out my other repositories for more systems engineering and data science experiments. | View All Repos β |
- MBSE: Capella, Eclipse, SysML
- Data Viz: Plotly, Matplotlib, ggplot2, ArcGIS
- LLM Ops: Google Gemini API, Prompt Engineering
- Simulation: Monte Carlo Methods, Vectorized Modeling
- LinkedIn: linkedin.com/in/abdullah-alghamdi
- Email: aalgha8@gmail.com