Alumni Spotlight: Zhi Yu, MHS, PhD ’20
Zhi Yu, MHS, PhD ’20, is an investigator, assistant professor at Massachusetts General Hospital and an affiliate faculty member at Broad Institute of MIT and Harvard.
Zhi Yu, MHS, PhD ’20, graduated from the Bloomberg School of Public Health with her PhD in Epidemiology and a concurrent MHS in Biostatistics.
Zhi received her Bachelor of Medicine from Hong Kong Baptist University and a Master of Science from the Harvard T.H. Chan School of Public Health. After graduating from the Bloomberg School, she completed a postdoc at the Broad Institute of MIT and Harvard. Currently, Zhi is an investigator, assistant professor at Massachusetts General Hospital, as well as an affiliate faculty member at the Broad Institute of MIT and Harvard.
Zhi recently received the 2023 STAT Wunderkind award, which celebrates the unheralded heroes of science and medicine. She has completed more than 60 publications and 8 preprints, including “Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases,” in the Journal of the American Society of Nephrology (JASN), co-written with her Bloomberg PhD advisors Josef Coresh and Nilanjan Chatterjee. This paper was one of two selected by JASN as the “Best of ASN Journals” in 2021.
Describe your current work in a way that will inform current and prospective students about career opportunities in biostatistics.
My research focuses on computational modeling of human multi-omics data to uncover the mechanisms driving cardiovascular and other age-related diseases, aiming to identify personalized strategies for disease prevention and treatment. For students interested in biostatistics, especially in health-related fields, roles like mine offer exciting opportunities to work at the intersection of medicine, data science, and public health.
What drew you to biostatistics and public health?
I've always liked numbers and have been good with them since I was very young. So, combining medicine with numbers naturally led me to epidemiology and biostatistics. I truly enjoy working with population data. To me, large-scale data from diverse populations is an incredibly powerful tool for understanding health and disease. And I love the potential impact this kind of research can have on improving health outcomes on a broad scale.
It's incredibly fulfilling to apply my biostatistics background to something I'm passionate about and to know that my work has the potential to make an impact in people's lives.
What has been your most satisfying job experience using your biostatistics background?
The most satisfying aspect of my job is being able to work with massive datasets and truly learn from the data. I focus on computational multi-omics research for cardiovascular and other age-related diseases, using population-level data to gain insights into how we can prevent and treat these conditions. It's incredibly fulfilling to apply my biostatistics background to something I'm passionate about and to know that my work has the potential to make an impact in people's lives. In other words, the satisfaction comes on two levels—first from the technical side and second from the real-world impact. I also love collaborating with brilliant, passionate colleagues. Every interaction is an opportunity to learn something new, which keeps me constantly growing in my work.
What led you to pursue your MHS in Biostatistics while concurrently working on your PhD in Epidemiology?
One of my PhD advisors, Josef Coresh, told me to do it, so I just did it! I'm very fortunate to have had fantastic advisors and mentors throughout my graduate and postdoc training, who have guided me in making several key decisions that have shaped my research trajectory.
What aspects of the Hopkins Biostatistics program did you find most useful?
The people and the skills. The Biostatistics department has a wonderful tradition of genuinely caring for its students. The faculty and fellow students were always sincere in teaching and helping each other, which made for an incredibly supportive environment. In addition to my PhD advisors, I also learned a lot from other faculty in the department, such as Scott Zeger and Hongkai Ji. Also, I'm still collaborating with some of my former classmates and lab-mates, and I've remained friends with several of them. As for the skills, they've been invaluable to my career, providing a solid foundation that I continue to build on in my research.
What reasons might you give to encourage a prospective student to get their MHS in Biostatistics from the Bloomberg School?
It opens up more possibilities and directions. For example, Nilanjan Chatterjee was my MHS advisor and later became my other PhD advisor, alongside Josef Coresh. At the start of my PhD, Joe was receiving large-scale proteomics data, and as I searched for an MHS advisor, I found Nilanjan an ideal mentor for advising me on omics data. Nilanjan's mentorship was invaluable and opened new possibilities for me. I began learning statistical genetics from one of the best in the field, Nilanjan, and he, along with his students, really helped me grow in that area. The computational multi-omics field is incredibly exciting and popular area these days. Beyond technical skills, Nilanjan has also played an important role in other aspects of my career. For instance, he suggested I work with my postdoc advisor, which led to a fantastic postdoc experience that added even more skills and perspectives to my research.