Shihao Yang

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Shihao Yang is a tenure-track Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. 

Shihao Yang received his Ph.D. in statistics from Harvard University in 2019, advised by Prof. Samuel Kou. He is currently a post-doc with Prof. Isaac Kohane in the Department of Biomedical Informatics at Harvard Medical School. His primary research interest is to harness the power of big data to solve real-life problems, with focus on three perspectives: methodological development, computational tools, and probabilistic modeling.

On methodology, he developed methods for infectious disease prevalence forecast based on internet search data, and built a tailor-made matching method to study cancer immunotherapy with electronic health data. On computation, he introduced a new method for parallelizable Markov chain Monte Carlo, and another fast approximation method for inference in dynamic systems. On probability, he proposed novel stochastic differential equations to capture the underlying dynamics of high-speed, high-volume financial market transitions.