I am a Data Science undergraduate at the University of California, San Diego.
Through my studies, I have come to understand the technical, domain, and ethical obligations
that come with working with data. Whether it be deriving insights through data analysis,
automating tasks through machine learning, or even telling a story through a visualization,
data science has truly become a passion of mine.
I have also had the great opportunity to share this passion of mine with hundreds of students as a data science tutor for various courses including DSC 10, 80, and 170. Along the way, I have further expanded my own understanding of data science and learned how to communicate its topics effectively.
During the Summer of 2019.., I interned at the San Diego Supercomputer Center under the direction of Ilya Zaslavsky. During my time there, I developed the ArcGIS Enterprise deployment for UC San Diego’s Bioregional Center GIS Gateway, a fully featured GIS for the visualization and analysis of spatial data. I later used Python to develop and implement user-friendly Jupyter Notebooks that enable users to interactively view, filter, analyze, and visualize data sets without the need to code. A generalized version of this project can be accessed below (Wrangler & Analyzer).
I have been invited back to the San Diego Supercomputer Center where I am now working on a research project in partnership with AEEC. This project focuses on the development of an end-to-end remediation performance model and remedial timeframe analysis tool to assess the effectiveness of Superfund site countermeasures.
Source code and comprehensive descriptions can be found on Github.