I specialize in optimization, embedded machine learning, and decision intelligence.
I build data pipelines and models that connect and optimize real-world systems;
from IoT telemetry to airfoil design with mathematical precision.
A selection of applied systems and research prototypes demonstrating measurable impact and technical depth. Each project blends data science, engineering, and optimization to solve problems that matter.
Research and Notes
Ongoing investigations into optimization, embedded intelligence, and physics-inspired learning. My research connects mathematical rigor with real-world performance.
Quantify and interpret short-term behavioral anomalies in national energy consumption preceding COVID-19 lockdowns.
Build a simple electricity demand forecasting model (e.g., GB grid 2020) and interpret its temporal drivers using SHAP or LIME.
Formulate and simulate a toy optimization problem for balancing electricity load during off-peak and on-peak periods.
Jan 2025
July 2024
July 2021