Heming Huang graduated from New York University in 2024 with a Bachelor’s degree in Honors mathematics. During his study,  Heming has established a solid foundation in  stochastic calculus, numerical analysis, mathematical modeling, and deep learning.  His academic pursuits included several research projects, leveraging techniques like deep learning and physiological modeling to address real-world challenges. Prior to joining the MSCF program, he worked as a quantitative research intern at CCB Principal Asset Management Company. There, he designed and implemented a reinforcement learning multi-factor model and utilized backtesting to validate its performance. Heming joined the MSCF program to enhance his financial computing skills and deepen his understanding of market dynamics. After graduation, Heming plan to pursue a career in quantitative research or quantitative trading.