Conducted extensive analysis on the implementation of solar power into underserved schools around Winston-Salem, NC.
Member of Wake Forest Engineering research team that identified feasibility of incorporating solar power projects into underserved communities in Winston-Salem, NC
Developed PyTorch-based neural network leveraging power consumption data from 149 North Carolina schools to evaluate cost-effectiveness of solar power implementation
Integrated machine learning model into MATLAB program to analyze and visualize yearly revenue and cost projections of photovoltaic systems, factoring in data of solar cost estimates and local weather
Compiled data into comprehensive report outlining methodology and outcomes of study
Shared findings using interactive GIS map and presented to environmental advocate
