Meet New Research Associate Ruiyi Zhang!

Ruiyi Zhang is a new NISS Research Associate who will be working with the National Agricultural Statistical Service (NASS). She received her Bachelor of Science degree in Mathematics from Nankai University in China and her Ph.D. in Statistics from Florida State University.  Prior to NISS, she was a postdoctoral fellow at Center for Imaging Science of Johns Hopkins University.  Her research interests include: computational statistics, computer vision, elastic shape analysis, functional data analysis and nonparametric statistics.

Why Statistics?

Ruiyi knew early on that mathematics was what she wanted to devote herself to. Her geometry teacher introduced her to the charm of math and as a result early on she spent a lot of time solving the geometric puzzles. She participated in Math Olympiads in senior high school but number theory and strategy problems were always a good challenge. 

After four years studying pure math in my undergraduate at Nankai University, I felt a little lost since I didn’t fully appreciate the reasons behind learning theories such as complex analysis or PDE.  So, I turned to statistics, a more applied and what I thought would be an easier field, which I have come to find was very naïve understanding.

Experience in Image Analysis

Ruiyi moved on to study shape analysis with manifold theory under the instruction of Professor Anuj Srivastava at Florida State University during her PhD.  This turned out to be a challenging and satisfying journey. From here she was advised to work with Professor Elie Younes at Johns Hopkins University to work on a more general field, medical image analysis, this work being immersed in applied math. 

Whereas when I applied to graduate programs, the field of statistics “looked” more applied and easier. However, I have come to find that you can never avoid things that you try to avoid!  My research during my PhD was shape analysis, which is an applied field that uses differential geometry as the main solution approach.  My past research focused more on the image data, and I would like to turn to data as numbers in the future. Luckily, NISS gives me the opportunity.

Future Directions

Statistics combines Ruiyi’s two favorite things together: math and coding. She likes to design algorithms with high efficiency. She once improved a code that was taking days to run so that it would complete the same task in several hours.  She derives an ample sense of satisfaction as a result of these kinds of accomplishments. Ruiyi highlights “grit” as an important quality that researchers need to demonstrate. 

Research is never an easy thing, and the people who survive perhaps are just the ones who didn’t give up!

She sees her greatest challenge as how to “hang in there” when she really wants to give up! Understanding the importance of this attribute developed as a result of being trapped by a problem for a long time and getting so tired of it.  She understands that the challenge is to find a way that she can step outside to look at the problem from other perspectives and find a way out.  

In her spare time she likes reading novels. Gabriel García Márquez and William Somerset Maugham are her favorite authors. 

Welcome to the NISS family Ruiyi!

Wednesday, May 4, 2022 by Glenn Johnson