I believe that the essence of life lies in our experiences and the measurements we take to understand them. In this sense, the financial market mirrors life itself: we are not only participants but also seekers of understanding. This perspective has driven me to pursue a career in quantitative research, where I can apply rigorous, data-driven techniques to form systematic understanding of the financial markets. I hold a Bachelor’s degree in Financial Engineering from Nanjing University and spent a year as an exchange student at UC Berkeley, where I took advanced courses in Statistics and Computer Science. My professional experience includes several quantitative research internships at hedge funds in China, where I worked on alpha research, machine learning for factor combination, and developing alpha backtesting frameworks. I also served as a research assistant at the Booth School of Business, University of Chicago, focusing on applying machine learning algorithms to asset pricing tasks, such as leveraging Autoencoders for dimensionality reduction and feature extraction. As a person, I strive to think independently rather than blindly follow established conventions and value long-term growth over short-term gains. I am seeking to join a firm that shares these values, where I can contribute my research capabilities and analytical skills to your success. Please feel free to connect with me via zoom or in person, and I am happy to discuss with you how I can contribute to your team.
