LinkedIn Profile I first discovered my interest in quantitative finance during my sophomore year. Through a stochastic processes course project, I saw how probability models could be used to understand financial uncertainty. During my undergraduate studies at NYU Shanghai, I built a strong foundation in mathematics, with a particular focus on financial mathematics. Training in economics and data science further helped me connect math modeling with market behavior and data analysis. Internships on both the sell side and buy side have shaped my quantitative skill set. On an equity-derivatives desk, I built Python pricing tools and incorporated Brownian bridge adjustments into standard simulation workflows to improve pricing efficiency. At leading Chinese quant funds, I worked on factor research and portfolio construction, applying machine learning and optimization methods. Alongside my industry experience, my research focuses on intraday volatility patterns, where I use high-frequency data to construct volatility indices and volatility risk premium measures in the Chinese options market. Beyond finance, I enjoy reading, photography, and hiking. I also value communication, which I developed through tutoring roles at NYU Courant and NYU Shanghai. I would be happy to connect with professionals in trading and quantitative research.
