LinkedIn Profile What does running a campus barbershop have in common with quantitative research? Both require identifying patterns, making decisions under uncertainty, and turning small signals into practical action. That connection is what shapes how I approach quantitative finance. I am interested in quantitative research, systematic investing, and machine learning, where rigorous analysis can be translated into investment decisions. During my undergraduate studies in financial engineering at The Chinese University of Hong Kong, Shenzhen, I built a foundation in mathematics, programming, and financial markets, and applied it through research and internships across equities, futures, and digital assets. My work has included machine learning-based equity prediction, patent-driven factor research, CTA futures strategy development, and crypto market research. These experiences taught me to test ideas carefully, evaluate model performance, and connect technical results with market intuition. Outside of research, I founded and operated a campus barbershop, which strengthened my leadership, communication, and execution skills. It also taught me that good decisions often come from observing behavior, understanding demand, and acting with discipline. As I begin the MSCF program, I look forward to connecting with professionals, alumni, and peers to discuss quantitative finance and how I can contribute to a quantitative investment team.
