I’m an Applied Mathematics & Statistics student at Purdue, focused on quantitative research and data analytics. I like turning messy real-world data into clean datasets, reliable pipelines, and decisions you can defend.
I built a factor momentum backtesting project in Python, covering data prep, portfolio construction, transaction costs, and evaluation. I also built XYZBudget, a plan-first personal budgeting web app with live variance tracking and subscription automation.
Right now I’m working on an AI syllabus policy analysis project at Purdue SPARK Lab: after scraping syllabi from R1 institutions and building a structured dataset, I’m now LoRA fine-tuning a language model to improve policy extraction consistency. I also write about what I’m learning — from oil markets to LLM fine-tuning.
I’m actively looking for internships in quant research, data analytics, and equity research, where I can apply math, statistics, programming, and clear communication to real problems.
Beyond work, you’ll usually find me watching anime, playing badminton, or hiking and exploring outdoors.