Summary
Chris Cai is a graduate student researcher and TA in Princeton's M.S.E. program with 11 years of experience bridging quantitative finance, machine learning, and mathematical research. He has applied deep learning architectures (CNNs, LSTMs, Transformers) and statistical testing to develop trading strategies during a quantitative researcher role and has research roots in algebraic and probabilistic problems from work at Madison Experimental Mathematics Lab. At UW–Madison he supported research spanning evolution, plant ecophysiology, and biostatistics, reflecting an unusual combination of computational skill and interdisciplinary science. Comfortable in Python and ML toolchains, he builds production-oriented backtests as well as exploratory models for academic inquiry. Based in New Jersey, he brings the rigor of a mathematics and CS background to pragmatic model evaluation and experimental design. Outside typical trajectories, he pairs high-frequency finance experimentation with deep theoretical curiosity, from matrix groups to model architectures.
11 years of coding experience
4 years of employment as a software developer
Talents Training Project Experimental Class, Talents Training Project Experimental Class at Tianjin No.1 High School
Bachelor of Science Mathematics and Computer Science, Bachelor of Science Mathematics and Computer Science at University of Wisconsin-Madison
Awesome Math Summer Camp Mathematics, Awesome Math Summer Camp Mathematics at Cornell University
M.S.E fully funded master program, M.S.E fully funded master program at Princeton University