Shengyu (Henry) Huang
Shengyu (Henry) Huang graduated from the University of Southern California with a major in Industrial and Systems Engineering and a minor in Business Finance. Before joining NYU, he has interned at the DHL eCommerce distribution center in Los Angeles and at May & Company -- a consulting startup firm located in Berlin, Germany.
After entering NYU FRE, he has discovered his research interest in applying machine learning techniques to finance in order to improve the accuracy of financial models and asset pricing. In summer 2020, he worked with Dr. Ken Perry on pricing Bermudan style swaptions under Libor Market Model, in which they utilized deep learning-based backward stochastic differential equation solver. He is currently working with Dr. Andrey Itkin on using deep learning to calibrate the ADOL model – a rough volatility model. These research experiences have made him realize the power of machine learning in the field of finance, so he became determined to apply for a Ph.D. program in finance and operations research. Coming from an industry-oriented program, he aims to bridge the gap between academia and the industry, developing models ready for industry use.
Believing in the philosophy of reciprocating, Henry enjoys helping his fellow peers. He has worked as a graduate assistant for the FRE department since he started the MFE program. He currently is also the Managing Director of Data Science at NYU’s FRE Bulls and Bears Club.