Contributed to the implementation of a scalable Machine Learning pipeline to predict and help residents of Johnson and Douglas Counties in Kansas at high risk of experiencing behavioral health crises. The Machine Learning Pipeline included an ETL pipeline using bash, Python, and PostgreSQL to load and cleanover 100 heterogeneous tables from a database. Utilzied Agile development aided by GitHub Projects and GitHub Issues for project management. This work was presented in a 3 minute talk on this work at DataFest 2022.

Helped students explore and enrich content during discussion sections through challenging problems and different problem solving methods, graded midterm and final exams

Lead review sessions, created review packets, taught an in class lesson on Partial Differentiation, demonstrated problem solving process in class to students.