Collect, clean, and analyze data to establish the spatial and statistical relationships between corporate homeownership and a variety of topics, including code violations, property tax appeals, and crime. Create web scrapers to collect power outage information for the continental United States, deployed and orchestrated using AWS. (Python, R, S3, Lambda, EventBridge, EC2).

Automated tax projections and anti-displacement payment reviews using Python, eliminating manual review for over 300 clients. Led analyses on equity, housing supply, and displacement risk to consult on community revitalization efforts across the Southeast. (Python, R, ArcGIS, Microsoft Office)

Collected, cleaned, and performed exploratory analysis on time series and geospatial datasets using Python, including pandas and scikit-learn. Modeled the causal relationship between weather patterns and India's power grid stability by training and analyzing OLS and vector autoregressive models. (Python, Spatiotemporal Models, Time Series Models)

Developed a predictive analytics model in Python to forecast component failure with 76% accuracy using pandas, scikit-learn, and PyTorch. Automated telemetry status alerts and common malfunction reports with Python, Excel, and Seeq. (Python, Microsoft Office)

Reviewed and implemented firmware designs for digital signal processing in VDHL, overseeing the full FPGA development lifecycle. Collaborated with supervisors to automate the standardization and conversion of configuration files using Python. (Python, VHDL, Xilinx Vivado)

Analyzed millions of GPS data points to create a model which classified pedestrian hazard incidents using MATLAB and Python. Collaborated with UIUC partners to research and visualize key performance indicators of a differential GPS system. (Python, Matlab)