- Modified previously underutilized algorithms to profile 500+ diffusion reactions to produce equivalent results at one-third of the computational expense- Expanded prediction capability by developing a machine-learned (SISSO) model on these profiled diffusion barriers- Coded python algorithm to perform a machine-learned materials screening process identifying kinetically promising solar thermal water splitting materials using VASP- Organized and queried generated data in the MongoDB NoSQL database- Constructed Matlab Monte Carlo models for efficient simulation of random diffusion processes- Management and optimization of quantum chemical programs on five supercomputers for the entire research group- Wrote a successfully funded proposal in collaboration with a small team

- Automated a manual 4 hour manual ArcGIS spatial analysis task to require minimal human input with python- Created data visualization for results of the above processes, and displayed them with HTML and CSS

- Collected and analyzed data to find optimal conditions for a cyclonic separation- Worked with manufacturing engineers to setup operating conditions to gather necessary data while balancing production requirements