Yu Shi discovered public health as an undergraduate in Hong Kong where she studied applied math and business. There, she entered — and won — a mathematical modeling competition that focused on the Ebola outbreak. After meeting professors in public health, she decided to pursue her Master’s in biostatistics. Now a second-year student at Yale, Yu has sought opportunities to explore different aspects of research in biostatistics.
As a research assistant with Professor Hongyu Zhao’s lab, Yu has studied de novo genetic mutations, specifically a statistical framework to quantify shared genetic components between complex diseases such as congenital heart failure and autism. Research in genetics involves a lot of data, explains Yu, and Bayesian approaches such as Markov chain Monte Carlo sampling and Metropolis- Hastings algorithm are applied.
Yu also works with Professor Denise Esserman in the Yale Center for Analytical Sciences where she is designing a two-stage randomized trial. While traditional clinical trials often ignore the role of a patient’s treatment preference on the response, the two-stage randomized preference trial design provides one approach for researchers to unveil preference effects from treatment effects. Yu will present her findings on this work at the Joint Statistical Meetings held by the American Statistical Association in July.
Yu has also been a teaching assistant for the Big Data course at the School of Management which teaches business students techniques and applications for analyzing data. She will begin her own studies at the School of Management next fall, as a doctoral student in Operations. She hopes to bring her interests in public health and business together through entrepreneurial enterprises.