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 →Built and optimized ML pipelines supporting data-driven decision systems. Ran end-to-end experiments across feature engineering, model training, and evaluation. Developed scalable inference components and integrated ML systems into production workflows. Contributed to model benchmarking and applied research.
Managed daily financial operations supporting 650+ student organizations with multi-million-dollar aggregate budgets. Performed budget reconciliation, variance analysis, and audit prep. Streamlined reimbursement and approval workflows using Oracle E-Business Suite and Concur.
Developed and evaluated quantitative trading strategies using Python and statistical modeling. Analyzed high-frequency market data to identify arbitrage and market-making opportunities. Worked on risk management, volatility estimation, and execution efficiency.
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.
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.
Founded digital health startup delivering home diagnostics and affordable care for Tier-2 Indian cities.