I am a master’s student in Financial Engineering at Korea University and expect to graduate in February 2025. I have participated in the epoxy project at AIML, where my primary role involved developing predictive models for material properties and using outlier detection techniques to enhance prediction reliability.

My research interest lies in quantitative trading using machine learning, focusing on utilizing LLMs for alpha generation. I am exploring alpha signal extraction from diverse financial data sources using state-of-the-art NLP technologies, specifically focusing on how LLMs can identify novel trading signals and improve investment strategies.

Before entering graduate school, I accumulated approximately eight years of experience in business management at Samsung Electronics. The COVID-19 pandemic prompted me to reconsider my career path and pursue advanced studies in financial engineering. I am dedicated to learning and applying AI techniques to contribute to quantitative finance. Additional details can be found in my resume.