- AI-Assisted Journaling (August, 2023 - December, 2023): Led team of three to create a web application for journaling.
We utilized the Chat GPT API for summarizing and leading the user’s journaling process.
I designed a user authentication system to facilitate a multi-user application use.
We also designed and deployed a SQL database with encrypted user journaling information on Google Cloud to facilitate recall.
- Tools used: Flask (Python), HTML, JavaScript, Bootstrap, MySQL, Chat GPT API, Google Cloud (GCP), GIT
- Analysis of Virginia Climate Legislation (November, 2021 - May, 2023): Analyzed Virginia state environmental bill and lobbying between 2015 and 2022.
Compared climate legislation to education and transportation legislation using Chi Squared Test of Homogeneity to check for uniqueness in bill passage rates.
Made dashboard visualizing the disproportionate effects of committees on bill passage rates.
Paper on findings currently Under Review.
- Tools used: R markdown, flexdashboard, plotly, neovim
- Personal Website (November, 2022): Created a personal website using Hugo.
- Tools used: Hugo, github pages, neovim
- Nvim Support for R Code (November, 2022): Built a plug-in for neovim that takes advantage of nvim’s integrated terminal-mode to process R code within the neovim session.
The plugin takes advantage of R’s syntax tree to allow the user to send logical lines and chunks of code to the terminal, replicating some behaviors of RStudio.
- Currency Profitability Model (February, 2022): Created a notebook with a team that used Q-Learning and self-made models to maximize profitability through purchasing either bitcoin or gold in late 2020-early 2021. Won a Meritorious Winner Award (top 8%).
The writeup can be found here
- Tools used: RStudio, \(\LaTeX\), MATLAB
- Show Recommendation System (Summer, 2021): Created a collaborative filtering recommendation system for Japanese animation which predicted the top-N recommendations
- Tools used: RStudio, vim, git
- Fruit Identification Neural Network (Summer, 2021): Created a convoluted neural network from scratch to classify between six different stale/fresh fruits
- Tools used: RStudio, vim, git
- Vespa Wasp Identification System (February, 2021):
Created a notebook with a team that used exploratory data visualization, Gaussian Naive Bayes, binary image classification, and frequency analysis models to identify Vespa Mandarinia wasps in Oregon.
The writeup can be found here
- Tools used: RStudio, \(\LaTeX\), MATLAB
- Data Visualization of Virginia Covid Cases (Summer, 2020): Created an exploratory data visualization notebook that graphed covid cases within Virginia