Quant-minded builder at the intersection of technology, finance, and data.
Passionate about leveraging technology and data science to solve complex problems in finance and beyond
Building intelligent systems that turn complex data into actionable insights, with a focus on real-world impact.
Designing predictive models and learning algorithms to uncover patterns and drive data-informed decisions.
Applying statistical modeling and analytics to understand markets, optimize strategies, and extract meaningful signals from data.
Developing systematic trading strategies and backtesting pipelines to model market behavior through code.
Investigating how information asymmetries and strategic interactions between market participants influence price discovery, trading patterns, and market efficiency in modern financial markets.
Working Paper →A parallel LLM orchestration system that asynchronously evaluates multiple models and synthesizes their reasoning into higher-quality outputs. Designed for scalable experimentation and automated model benchmarking.
A computer vision platform that evaluates rooftop solar potential using satellite imagery and NASA climate data, enabling large-scale feasibility analysis across 10K+ square miles.
Interactive simulation platform modeling economic policy impacts. Being tested by UCSD Economics Department.
Alternative credit scoring using non-traditional signals. 20% improvement in classification accuracy.
Real-time facial emoji mapping using CNN pipelines and deep learning for human-AI interaction.
Developed end-to-end ML pipelines spanning feature engineering and experimentation, reducing model iteration time by 30%. Contributed to applied ML research in high-velocity startup environment.
Automated budget approval workflows for 650+ organizations using Oracle APIs. Built financial forecasting models for high-value event budgeting.
Engineered data pipelines for large-scale financial datasets, increasing backtesting throughput by 40%. Implemented automated validation and DAG-based ETL workflows.