Student Profile: Sen Zhao

Quick Facts

  • PhD program
  • Year entered program: 2012
  • Hometown: Beijing, China
  • Advisor: Ali Shojaie

Why did you choose biostatistics?

I was a math major at college and have always wanted to utilize my mathematical training to help scientists solve real world problems. During the summer of my third year in college, I went to the University of North Carolina to conduct research in biostatistics. At that time, I discovered my passion in biostatistics.

Why did you choose the UW?

I was interested in statistical machine learning when I applied to graduate schools, and I felt that my personality and work style fit better with younger faculty members. UW had two of the best junior professors in the field at that time, Ali Shojaie and Daniela Witten. It was a simple decision for me.

How would you describe your experience as a UW Biostatistics student?

The first two years were very challenging because we needed to take classes and conduct research at the same time. But it was also very rewarding. I joined the Statistical Learning Applied to Biostatistics Lab (SLAB LAB) in my first year.  Over the past five years, I've received a lot of help and support from lab members.  There are many great mentors and friends in the program who have helped me make the most out of my time there.

What kind of research are you doing?

I am developing hypothesis testing methods for high-dimensional linear, graphical and time-series models. Estimation methods with high-dimensional data have been extensively studied in the past two decades. However, very few of these estimation methods provide measures of uncertainty, such as p-values or confidence intervals, which are crucial for drawing scientific inferences. Throughout my PhD studies, I have worked with Ali Shojaie on several projects regarding high-dimensional hypothesis testing methodologies. They have numerous applications in genomics, phylogenetics and neuroscience. Besides high-dimensional inference, I am also broadly interested in machine learning, causal inference and longitudinal data analysis.

How would you describe the benefit of your research?

My research addresses statistical challenges of analyzing high-dimensional data in order to help researchers better understand the biology of diseases. Recent technological advances have resulted in the collection of high-dimensional data in several scientific fields. The common feature of these data is that the number of variables measured for each sample is usually much larger than the number of samples. For example, genetic datasets are usually high-dimensional in the sense that we have measurements on more genes than individuals. Emerging high-dimensional data offer new opportunities for scientific discovery. By using high-dimensional genetic data we could find genes that cause cancer, and thus design more effective diagnostics and treatments. Unfortunately, due to the high-dimensionality, most classical statistical approaches that are developed in the past century are invalid for analyzing such data.

What are your future goals?

After graduation, I will join Google Research as a statistician to conduct research on machine learning. Although it is not directly related to public health, I hope my contribution could still benefit the lives of millions of people.

What do you like most about Seattle?

I love Seattle’s natural beauty! Seattle is within 100 miles of three national parks, which makes it a heaven for outdoor lovers. I think it might be the only big city on earth that within a 2-hour drive, you can see the ocean, rain forests, snow mountains, scablands, killer whales, marmots and black bears. Also, summers in Seattle are truly lovely.

What extracurricular activities do you enjoy?

Besides outdoor activities, such as hiking, kayaking and road trips, I like to watch movies and Real Madrid and Seahawks games. Every year in May or June, Seattle hosts the annual Seattle International Film Festival (SIFF).  Some good foreign films and documentaries choose to debut here and go on to win many awards. I am also a foodie and Seattle offers numerous good Japanese and Italian restaurants.

What advice would you give to a student who is considering a UW Biostatistics program?

I think the most important factors to consider when choosing a biostatistics program are the rigor of its coursework (especially theoretical courses) and the expertise of faculty. UW Biostatistics definitely offers both.  Our theory courses are challenging. As I’ve progressed through my PhD study, I began to realize how lucky I was to have received such rigorous training. It has made reading methodological papers and picking up new ideas much easier.  We also have world-class researchers in various areas.  For me, my advisors and collaborators are not only outstanding mentors who share their research perspectives with me and guide me through obstacles, they are also great friends.

March 17, 2017