I'm a Statistics & Data Science student at UC Santa Barbara who likes turning messy datasets into clear answers.

I'm an undergraduate studying Statistics and Data Science at UC Santa Barbara, where I'm fascinated by turning messy, real-world data into meaningful insights. My interests span machine learning, artificial intelligence, and statistical modeling, and I enjoy solving problems that sit at the intersection of data, technology, and decision-making.
Whether I'm building models in Python or exploring new research ideas, I'm always looking for opportunities to learn and create.
Previously, I worked as a Data Analytics & SEO Strategy Intern at Taboola, where I analyzed search performance, competitor trends, and large-scale web data to help guide strategic decisions. I'm currently an AI Research Assistant at UCSB's Center for AI & Society, exploring applications of AI through research while continuing to expand my technical skills.
Outside of academics, I work as a campus tour guide, helping prospective students experience everything UCSB has to offer.
Analyzed career length across 4,486 NBA players using injury logs, box scores, and season stats. Modeled survival with Kaplan-Meier curves and Cox regression, compared against OLS and logistic regression, and used K-Means to cluster player archetypes. Built and delivered a presentation with a research partner.
An interactive tool that turns any first name into a data-driven profile: living-age distribution weighted by SSA actuarial survival tables, a full 1880–present popularity arc with trend-archetype classification, cosine-similarity "name neighbors," and a US geographic over-index map. Built from real SSA national and state baby-name data.
Currently working as an AI Research Assistant in Professor David Lawson's lab. Write-up coming once the project reaches a shareable stage.
More projects coming soon.
Open to internships, research collaborations, and graduate program conversations.