Ziyu Ji

Biostatistics PhD

"I thought it would be interesting and different to work with an entertainment and internet-focused industry. It’s been a unique and rewarding experience being able to apply my data science knowledge [at Netflix]."

First, I’d like to know a little bit about you as a person. Where did you grow up? Where did you attend undergrad and what was your degree/area of study? [Ziyu] I grew up in Beijing, China, and went to Shanghai for my undergrad in mathematics when I was 16. Then I went to the U of M School of Public Health for my Master of Science in biostatistics and decided to stay here to get my PhD.

What drew you to public health? [Ziyu] Both of my parents work in health-related fields, and so I heard a lot of different stories growing up about how the human body works. I have felt very connected to medical science since I was young, but I did not commit to it, or public health, until my grandma got diagnosed with lung cancer. She didn’t have any high-risk factors, but our whole family still regrets not seeing the warning signs earlier. I decided that public health was a meaningful path for me, so that I could help prevent diseases at early stages. Since I had studied mathematics, I thought that biostatistics would be a good combination of my passion and skill set.

Ziyu Ji, Biostatistics PhD student
Ziyu Ji, Biostatistics PhD student

Where are you completing your applied practice experience, and who is your preceptor? [Ziyu] While pursuing my PhD, I have had two different internships. I worked as a biostatistician at Takeda Pharmaceutical Company last year, where I did a research project on developing the method of selecting optimal sample sizes for clinical trials on pediatric or rare diseases. In the summer of 2022, I worked as an Experimental & Causal Inference Intern at Netflix, which involved the data analysis and methodology study related to large-scale experiments with complex structures.

Why did you choose Netflix? [Ziyu] I thought it would be interesting and different to work with an entertainment and internet-focused industry. It’s been a unique and rewarding experience being able to apply my data science knowledge into a setting like this.

What were you focused on at the company? [Ziyu] Unfortunately I can’t share too much because it’s currently top secret for Netflix! But my work was with the data science and engineering team, where they focus on growth and pricing, which helps inform product and business decision-making at Netflix. I worked on building models and analyzing the results from our experiments to help the company make better decisions going forward.

Have your internships influenced your next steps in public health? [Ziyu] What I was working on at Netflix was not directly related to public health, but the methodology framework I was developing could potentially help experiments in public health as well. I was working on a tool that could be applied to public health projects and help innovate the way in which we approach the similar type of health data in the future.

Why did you choose to come to the U of M School of Public Health? [Ziyu] I chose the School of Public Health because I was interested in health and promoting the well-being of a large population. U of M SPH has a comprehensive biostatistics program, and when I learned more about it, I knew that it was the right fit for me. My research advisor, Julian Wolfson, has been the best advisor I could ever imagine and he was one of the key reasons for me to come back for PhD after graduation. Also, unlike a lot of people I’ve met, I like the winter! So Minnesota was a good choice.

What do you like about your current program? [Ziyu] Because I have been in Minnesota for six years and completed my Master’s here, it almost feels like this program is a part of me. I feel like an essential part of the program, too. The coursework is helping me grow as a statistician, and the teaching style here is very different from what I grew up in, so it’s been a great learning experience. The faculty are very supportive, and I have been given such great academic and personal support. My cohort, classmates, and the people around me are very warm and welcoming. When pursuing a PhD, sometimes it can feel lonely and difficult when you are entrenched with work. So having a support system at the school makes a huge difference.

What has been your favorite class so far? [Ziyu] My favorite classes were PubH 7440 Introduction to Bayesian Analysis taught by Professor Lin Zhang and Bayesian Decision Theory and Data Analysis taught by Professor Eric Lock, both contribute to my current research interest. The first gave me important context and motivation, whereas the second one helped build my expertise and knowledge. 

What do you like about being in Minnesota? [Ziyu] I really consider this my second home. I really like how nice and kind the people are here. Almost everyone I have encountered has been really friendly and helpful. I also like the natural environment of Minnesota and the activities related to the outdoors. I am even considering settling down here after graduation because I like it so much!

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