I am developing Machine Learning and Deep Learning models for evaluation the energy performance to detect and diagnose the simultaneous multiple faults in the HVAC systems of the commercial buildings which accounts for about 40% of the total energy use in the US. I use Python with Scikit-learn, TensorFlow, PyTorch, and Keras libraries for the development of models, as my PhD thesis. Also, I am a data scientist skilled in programming with Python and SQL (pgAdmin) for data analysis.
Moreover, I Developed machine learning models using historical data of HVAC system of two semi-detached houses located in Inuvik, NWT, Canada and weather data for prediction of heating energy use and developed the Principal Component Analysis (PCA) model for fault detection and diagnosis scope in the HVAC system as my MASc thesis.