Prior to joining ISyE, he served as a postdoctoral researcher in the Department of Biomedical Informatics at Harvard Medical School. His primary research interest is to use big data to solve real-life problems focusing on three perspectives: methodological development, computational tools, and probabilistic modeling. He has developed methods for infectious disease prevalence forecasts and built a tailor-made matching method to study cancer immunotherapy with electronic health data. He also introduced a new method for parallelizable Markov chain Monte Carlo and another fast approximation method for inference in dynamic systems.

Yang received his Ph.D. and an A.M. in statistics from Harvard University and his B.Sc. in actuarial science from University of Hong Kong.