Shiran Yuan, a 16-year-old student from Duke Kunshan University, won the Best Paper Award at this year’s International Conference on 3D Vision in Davos, Switzerland.
At the cornerstone event for advancing optical sensor technology, which took place from March 18th to March 21st, Yuan presented a ground-breaking research paper that uses tensor decomposition to improve visual precision while using computing power best.
The event gathered researchers from top universities like Stanford University, Carnegie Mellon University, and ETH Zurich, but Yuan’s work stood out because it used a new way to develop imaging models that could be used in a variety of situations.
The paper’s corresponding author and co-recipient of the award was Dr. Hao Zhao, an assistant professor at the Institute of Intelligent Industry at Tsinghua University.
Yuan, who started at Duke Kunshan when he was only 13, said that the liberal arts education and the opportunity to learn with students and scholars from around the world have helped him a lot.
Yuan said, “I got to where I am now with the help of Duke Kunshan’s unique blend of flexibility, support, and international perspectives. “
“I’ve had access to a wealth of academic resources and the chance to interact daily with leading scholars from various backgrounds.”
Yuan has been able to delve into different disciplines over the past three years, with a particular focus on Applied Mathematics and Computational Science.
Faculty and students at Duke Kunshan University come from about 70 different countries.
Yuan also thanked Dr. Kaizhu Huang, who was his Signature Work project advisor and a professor of Electrical and Computer Engineering at DKU, for carefully guiding him in many areas, such as learning the latest technologies, understanding academic protocols, and developing scientific research methods. The student said Huang’s love of learning has always inspired him.
Signature Work is an important part of DKU’s new, innovative undergraduate curriculum. It requires students to research an original topic independently and use creative, problem-solving thinking to answer important real-world questions.
Yuan and Huang are revising another academic paper about tensor completion that they hope will be accepted by a top international journal.
Yuan has already finished all of his degree requirements, one year ahead of schedule. He plans to attend Duke University for a master’s degree in engineering.
“Science constantly pushes the bounds of possibility, and I’m excited to see where science takes me next,” Yuan said.
