Building at the intersection of quantitative methods, machine learning, and financial systems.
Stochastic calculus, martingale theory, statistical learning, econometrics, linear algebra, convex optimization, real analysis, abstract algebra
Python, PySpark, Airflow, SQL, AWS, GCP, TensorFlow, PyTorch, Docker, FastAPI, Scikit-learn, Pandas, NumPy
Market microstructure, backtesting, risk modeling, trading strategy research, options pricing, financial modeling, market data pipelines, credit analysis
Investigating how information asymmetries and strategic interactions between market participants influence price discovery, trading patterns, and market efficiency. Building on Kyle (1985) and Glosten-Milgrom foundational models.
Working paperUC San Diego, San Diego, CA
UC San Diego, San Diego, CA
Parallel LLM orchestration for asynchronous multi-model evaluation and reasoning synthesis.
GitHubCV platform for rooftop solar potential using satellite imagery and NASA climate data across 10K+ sq miles.
DevpostInteractive economic policy impact simulation. Tested by UCSD Economics Department.
2nd Place UC San Diego, 2024
2nd best overall, HackPrinceton Fall 2025
Awarded with $1,000 scholarship per quarter for working on my research project.
Awarded 6 times for outstanding academic performance.