I am a Physics, Mathematics, and Computer Science student at the University of Florida interested in quantitative research, machine learning, scientific computing, and financial markets.
- Conducting machine-learning research on solar-wind regime identification using Solar Orbiter and ACE observations; manuscript in preparation
- Building quantitative-finance projects involving derivatives pricing, market microstructure, and stochastic simulation
- Strengthening my background in probability, stochastic processes, algorithms, and software development
An event-driven, synthetic-data market microstructure research project focused on order-flow simulation, execution costs, and inventory-aware quoting:
- Price-time-priority order matching
- Market and limit orders
- Order-book imbalance signals
- Passive and inventory-aware market making
- Adverse-selection analysis
- PnL attribution
- Reproducible synthetic backtests
A reproducible Python derivatives-research project focused on stochastic simulation, variance reduction, and benchmark validation:
- European and Asian option pricing
- Black-Scholes validation
- Antithetic and control-variate methods
- Sobol quasi-Monte Carlo
- Monte Carlo Greeks estimation
- Implied-volatility and volatility-smile analysis
- Interactive exploration with delayed demonstration option data
Languages: Python, Java, C++, SQL
Machine Learning: scikit-learn, CatBoost, clustering, dimensionality reduction
Scientific Computing: NumPy, pandas, SciPy, Matplotlib
Tools: Git, GitHub, Jupyter, Tableau
Quantitative research · Algorithmic trading · Machine learning · Stochastic processes · Scientific computing · Space physics · Neural ODEs