Just after Rachel Chen took her first advanced mathematics class at Cary\u2019s Green Hope High School, she knew the probability was quite high she would study statistics.<\/p>\n
\u201cI always really liked math when I was young,\u201d Chen says. \u201cI knew I wanted to pursue a career related to it. Then I took an Advanced Placement statistics class when I was a sophomore in high school and really enjoyed that.<\/p>\n
\u201cIt was like the more applicable version of math.\u201d<\/p>\n
So she came to NC State, which was not only near her hometown but has one of the nation\u2019s oldest and premier statistics departments, to pursue a degree that will lead her into a research career in precision medicine.<\/p>\n
And the sophomore Goodnight Scholar has excelled.<\/p>\n
Recently, Chen was one of four NC State students to win a prestigious Goldwater Scholarship, which provides up to $7,500 per academic year for promising scientists and engineers.<\/p>\n
Chen got a head start on her research career after her freshman year, when she participated in a National Science Foundation-funded summer statistical genetics research program at Dordt College in Sioux Center, Iowa, under the supervision of Professor Nathan Tintle.<\/p>\n
\u201cWe were analyzing genetic data, and I worked on a human genetics project and a bacterial genetics project,\u201d she says. \u201cAt the end of the program, my mentor suggested I submit a paper to the Pacific Symposium on Biocomputing.\u201d<\/p>\n
She, in fact, was part of two peer-reviewed journal publications, which led Tintle to recommend that she apply for the Goldwater. One of 496 winners from across the country, Chen is ready for her next summer research adventure. She leaves in early June for Fairbanks, Alaska, where she will study mathematical models of glacial ice flow.<\/p>\n
And while Chen is focused on a career in statistics research, with hopes of earning a Ph.D. in biostatistics, she has spent much of her time at NC State expressing her artistic side. An accomplished artist, she paints in her spare time, exploring the subtle similarities and vast differences between math and art.<\/p>\n
\u201cI was interested in math and art early on, but I think that for most of my life, I developed these interests separately from each other,\u201d she says. \u201cThe artistic side of me isn\u2019t necessarily an escape from the mathematical side, but I think that having both interests helps me develop into a more well-rounded person.\u201d<\/p>\n
However, she did learn in her first art class that precision is as much a part of painting as it is permutations.<\/p>\n
And she liked it.<\/p>\n
\u201cIf I was working on an assignment and basing it off a photograph, which is almost always the case, I would have to scale the original image,\u201d she says. \u201cI tended to be very meticulous about this, and I think it came from wanting to make the proportions or dimensions of every part of the image precise.<\/p>\n
\u201cI would take measurements and quantify parts of the piece instead of just eyeballing the original image to make sure I was on track like the other people I knew.\u201d<\/p>\n
Her artistic side also helped her develop an interest in data visualization. She particularly enjoyed the work of Canadian data artist Jer Thorp at a science\/design crossover event NC State hosted last year.<\/p>\n
\u201cThese more creative visualizations have shown me interesting ways to think of and combine more mathematical\/logical qualities with visual qualities,\u201d she says. \u201cI would love to explore this more in the future.\u201d<\/p>\n
Chen also participates in performance art, as a member of a campus lion dance troupe that has been dormant for the last year. The dance, which mimics a lion\u2019s movement, is popular in Chinese and other Asian cultures around the Lunar New Year. Chen, of Taiwanese-American descent, has performed the dance since high school with friends, and is part of the reactivated Nine Star Lion Dance Troupe that performs for local businesses and for student and community organizations.<\/p>\n