I am a doctoral researcher working across solar photovoltaics, machine learning, thermal modeling, and data-driven energy analytics. My work focuses on making PV systems easier to monitor, explain, and improve through trustworthy data pipelines and applied AI.
- Machine learning for solar energy systems
- PV anomaly detection and performance analytics
- Thermal modeling for outdoor PV operation
- Forecasting, data quality, and decision-support workflows
- Domain-specific AI tools with provenance and citations
Python | scikit-learn | FastAPI | Flask | Streamlit | SQL | MATLAB | Linux | Git | MLFlow
I develop research-oriented prototypes that connect solar-energy domain knowledge with machine learning, knowledge graphs, explainable analytics, and practical interfaces for scientific insight.


