Competing in kickboxing taught me to seek out difficult challenges, remain composed under pressure, and adapt when conditions change. That mindset is one reason I am drawn to quantitative finance, where complex problems require rigorous analysis and decisive action. I am particularly interested in systematic trading and quantitative research, where I can combine financial modeling, data analysis, and software development in a fast-paced environment. I studied electrical and computer engineering and mathematics at Rutgers University, where coursework in computational finance, probability, artificial intelligence, parallel computing, and signals taught me to approach problems from both a quantitative modeling and systems-building perspective. Through my academic and technical work, I have used Python and C++ to analyze data and build systems ranging from AI applications to performance-sensitive software. Working across manufacturing, research and development, software engineering, teaching, and entrepreneurship has shown me how businesses make decisions, allocate resources, respond to constraints, and adapt to changing conditions. That exposure has strengthened my interest in markets as a way to understand how industries, companies, and the broader economy interact. I will be based in New York City and welcome the opportunity to connect virtually or in person with professionals working across quantitative finance. 听
