• Working with Professor Monica Valluri on using data science to analyze galactic dynamical models• Built a program to automatically determine key resonances in stellar orbit distributions, enabling individual orbits to be automatically classified. • Helped build an algorithm to classify the orbits of stars based on various characteristics, such as angular momentum, orbital period, and pericenter radius• Utilized numpy, pandas, and orbit integration libraries to examine the resonance distribution of 100,000 orbits in barred galaxy simulations, identifying the role different resonances had in supporting galaxy structure

• Built a Ruby on Rails memory profiling application that broke down the memory usage of API endpoint calls• Parsed and analyzed the memory profile of an internal application, locating areas of extreme memory usage• Reduced the memory used from certain endpoint calls by almost 90%, significantly reducing server response time, and eliminating overload and timeout responses• Helped restructure an internal application to utilize docker, building containerized versions of various backend applications, and ensuring new containers would spin up automatically if additional memory was needed

• Built a logging service that reformatted and routed 100,000+ events from internal systems to storage servers• Learned about and implemented multiple IAM protocols, including OpenID, OAuth, and LDAP• Gained critical experience working with a software development team, integrating agile development and CI/CD into the working process, including designing gitlab job stages and publishing to various pipelines