I studied Mathematics at New York University, where I built a rigorous foundation in mathematical thinking. Alongside my undergraduate coursework, I sat in on graduate courses including Probability Theory, Statistics, and Stochastic Calculus. Seeing how these ideas could describe uncertainty, systems, and real-world decisions made me increasingly fascinated by the applications of mathematics.
That interest led me to Computer Science at Seoul National University, where I joined the Optimization Lab. There, I have been able to study and research a wide range of mathematical applications, with particular focus on genetic algorithms, neural networks, and financial engineering. This path has let me connect theoretical tools with practical problems in optimization, machine learning, and finance.