
Hey! I'm currently a senior at Vanderbilt University studying Applied Math & Computer Science. From a very young age, I've always had an interest in the financial markets, after watching The Big Short with my dad, and understanding absolutely NONE of it the first time.
Simultaneously, I had a passion for prediction. It all started with my dad asking me to take guesses on behavior, and when time came to learn how to drive, instead of typical questions such as "what do the double yellow lines mean," he had a penchant for asking questions along the lines of "what's the car to our left going to do next?" Naturally, I found my way to the field of machine learning and data science when posed with such tasks, and utilized those skills in various different fields, with projects ranging from Parkinson's Disease diagnosis to forecasting sector returns using LSTM.
Outside of financial markets and data science, my hobbies include long-distance running, weightlifting, tennis, comic-books, stand-up comedy, and devouring Chili's Triple Dippers.
Equity Risk division. Part-time during Fall 2026 semester.
Macro and Fixed Income pod, researched signals for systematic strategies, developed internal software and tools.
Conducted backtests on strategies, signals, indicators, for position entry/exit, sizing, and risk management. Also performed in-house software development, ad-hoc analysis using alternative data, to find alpha-generating sources of information.
Data preprocessing and handling of fasta files for genetic sequences. Worked with ABSD database of 1.3 million+ RNA sequences. Utilized ProgenV2-oas LLM model for antibody discovery.
Utilized Monte-Carlo method for simulating commercial real estate investment properties success under various market factors. Conducted internal software development & IT solutions.
Ideated machine learning and cloud migration solutions for nonprofit organization that provides low-cost auto loans to underserved demographics. Project completed as part of 180 Degrees Consulting @ UT Dallas.

Tool to monitor portfolio risk and analyst performance for the Owen Student Fund, Vanderbilt's premier student-run investment fund with $150K+ AUM. Used by 15+ investment teams.
Full-stack proprietary web application tailored to firm's research needs. Equipped with position signaling, equity recommendation, screens, backtests, and portfolio risk management tools. Screens on 10,033 SEC-registered tickers and signals on L/S positions of $1.2–10M.

High-frequency trading algorithm that utilizes offline Reinforcement Learning on IEX data spools to backtest trading order momentum.

Full-stack web application capable of crafting user portfolios tailored to risk limits, growth, sectors, etc.

Multimodal approach to Parkinson's Disease (PD) diagnosis using ensemble ML, full-stack application to simulate user experience.