Projects

I participated in the UCLA Computational and Applied Mathematics REU (Research Experience for Undergraduates), funded by the NSF, in summer 2023. I collaborate with a team of 4 to conduct research, design 10+ experiments, build PDE solver with numerical analysis, optimize code, and create visualizations. Under the mentorship of Mason Porter and Sarah Tymochko, we simulated opinions dynamics in a mathematical network with an adaptive Deffuant–Weisbuch model in Python. We presented our poster at The Joint Mathematics Meetings (JMM) 2024 and here is our final proejct presentation....

I worked with a team of 8 and implemented extractive text summarization with TF-IDF from scratch and with sklearn. Feel free to check out our GitHub, Streamlit demo, and Medium article.

I worked with Professor Mason Porter from UCLA’s Math Department on social network analysis, where I modeled a network to examine online community sentiment and behaviors (45k+ posts) under COVID lockdown. After extracting posts through requests and API, I conducted EDA and modeled the network using NetworkX. To examine users’ sentiments, I developed a deep learning sentiment analysis model for Mandarin Chinese text and achieved an 80+% accuracy. Check out my research proposal here or take a peek at my code base here....

I’m working with Professor Steinert-Threlkeld from UCLA’s Public Affairs department to analyze if a superlinearity exists between city population and protest sizes. We are using ACLED dataset for protests across the world and Geonames for population. So far, no correlation has been found between the 2 variables. Feel free to check out the GitHub repo.

In this project, I explored Oil Prices for the past 6 years (source) utilizing ARIMA and an state-of-the-art time series linear model. Check out my presentation here for to see the results. My ARIMA model achieved an MSE of 5.88 and < 0.01 for LSTF. Here’s the code for ARIMA models: GitHub repo.