I am a Data Science undergraduate and tutor 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.
As a data science tutor, I have had the opportunity to share this passion with hundreds of students through various courses, such as DSC 10, 80, and 170. Along the way, I have both 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. I worked on developing 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.
I have been invited back to the San Diego Supercomputer Center to work on a research project where I will be developing Python notebooks to compute performance remediation models and visualizing its results spatially.
Jupyter Notebook allowing users to interactively view, filter, analyze, and visualize data sets
through a series of widgets.
Tools: Python (Holoviz & Pandas)
Depicts the energy production & consumption of
Springfield (from The Simpsons).
Project demonstrating a framework to predict the traffic impact of an event in San
Diego. Includes research, data cleaning, and data analysis. Coauthored with a
Tools: Python (ArcGIS API and Pandas)
Houses projects dedicated to the improvement of San Diego communities.
Allows users to analyze San Diego based spatial data interactively or programmatically.
Tools: HTML, CSS, ArcGIS Enterprise