About
I'm a quantitative developer with a passion for building systems that operate at the intersection of traditional finance and emerging blockchain technologies.
Currently pursuing dual degrees in Economics and Mathematics at Penn State University, where I've developed a strong foundation in statistical analysis, mathematical modeling, and algorithmic thinking. My academic work focuses on game-theoretic models of retail trading behavior and market microstructure.
My professional experience spans traditional financial markets and decentralized protocols. At Cboe Global Markets, I prototyped low-latency data pipelines and benchmarked feed handlers for high-frequency trading systems. This experience gave me deep insights into market data infrastructure and the importance of microsecond-level optimizations.
In the blockchain space, I've built real-time trading bots for Solana's DeFi ecosystem, focusing on automated market making and momentum-based strategies. These systems process hundreds of transactions per second while maintaining strict risk management protocols.
I'm particularly interested in the mathematical foundations of market behavior, from order flow analysis to the game theory behind algorithmic trading strategies. My research explores how retail traders' behavioral patterns can be modeled and predicted using agent-based simulations.
- • Putnam Mathematical Competition participant (2023, 2024)
- • Market Data & Access intern at Cboe Global Markets
- • Built production trading systems processing $100K+ daily volume
- • Math Club board member and competitive programming enthusiast
- • Research in game-theoretic models of retail trading behavior
Working on research into event-driven market models and building more sophisticated risk management systems for DeFi protocols. Always interested in connecting with others working at the intersection of mathematics, finance, and technology.