Making Waves in Industry and Academia - Profile Yiran Shen

First generation college student and PhD candidate at the Oden Institute for Computational Engineering and Sciences, Yiran Shen, talks about her recent internship experience at Dell Technologies.

“I’m a very boring person,” claimed Yiran Shen, first generation college student and PhD candidate at the Oden Institute for Computational Engineering and Sciences. “I don’t have any crazy hobbies or unique skills - like being able to say the alphabet backwards or anything like that.” Shen shrugs apologetically. 

Behind Yiran Shen’s desk at the Oden Institute, there is a floor-to-ceiling whiteboard extravagantly painted with colorful dry-erase equations and the characteristic arrows and bubbles of a neural network, the physical representation of a series of machine learning algorithms that root out the deeper relationships in otherwise inscrutable sets of data, like synapses stretching between a brain’s neurons and paving the future of computational science.

Apparently, humility is the key to success. While some of us remain focused on trying to remember which letter comes before Q in the alphabet, Shen is modeling seismic waves deep beneath the ocean and solving real world problems through one of Dell’s coveted summer internships. 

“I’ve stayed at school for a long time, so working with Dell was quite a different experience compared to student life. My day-to-day was just trying to deliver the algorithm on time,” said Shen. “It was a big project, but we only had three months for the internship, so we just needed to work hard. I was swimming every day at the UT gym. If there was something I was missing, if there was a bad output… if I cannot overcome the questions, I swim.”

As the first member of her family to attend college, Shen is no stranger to making waves. Since the leaves turned, signaling the end of her internship, she’s been swimming over her doctoral thesis at the Oden Institute: the computational science behind optimal transport for full wave inversion, a robust and high-resolution tool for modelling seismic waves in the earth.

“My family just wants me to keep studying,” she laughed. “They tell me, ‘Go and keep studying!' During my undergrad at UT, I studied finance and mathematics, but my specific topic was numerical analysis. It was a very smooth road to computational science. When you study mathematics, it’s composed of two parts. The first is pure math, all about writing down your theories and trying to prove them. The other is applied mathematics which is all about engineering because, in the end, a lot of engineering is just equations,” Shen explained. 

“I’m a good fit for applied mathematics because it lets me make myself useful. When I talk with friends about mathematics, no one understands what I’m saying. But by telling them what can be overcome with mathematics, I can convey its importance. I tell them, ‘I’m the one who helps people see down through the ocean to what is beneath the seafloor,’ and they go ‘Ah!’”

“It’s very important to go outside academia and see what people do in normal companies when they have your kind of background,” she counseled. “Honestly though, I want to stay in academia a little longer. In industry, you have several tasks that you promise to deliver, so you just have to focus on those tasks. In academia, it’s easier to soak up knowledge. If you can see some exciting question that no one is asking yet, you can turn around and ask it with your friend, with the graduate students around you.”

Shen is hoping to publish a paper this year on her computational geophysics research with her advisor, Dr. Bjorn Enquist. Though her backstroke might suffer for it, her future looks bright.