Undergradutes from School of Earth Sciences Won Second Place in COVID-19 Computational Challenge

2020-06-24 Global Communications

Undergraduate student Jia Pengyue led the team Contemporary Li Shizhen and won the second place of the 2020 COVID-19 Computational Challenge which was jointly organized by the RMDS Lab (Research Methods and Data Science Lab) and the City of Los Angeles. “This challenge has been a way to bring the best ideas from our global community and to focus on how innovation, data and technology can help us address this global crisis together.” said Jeanne Holm, the City of Los Angeles Chief Data Officer, in an interview. 408 participants from Asia, Europe, Africa, and North America, including high school students, college students and scientists, joined the Challenge.

At the online award ceremony held on zoom, the Deputy Mayor of the City of Los Angeles, Miguel Sangalang, presented the award to the team. The team received $1,000 cash and internship opportunities from the City of Los Angeles, Computational Medicine Department of UCLA and some other partners of the Challenge. The research conducted by the team will be recommended for publication in Harvard Data Science Review and will be showcased at the 2020 Innovative Methods with Data Science & AI Conference (IM Data 2020).

Contemporary Li Shizhen is a team composed of undergraduates from Zhejiang University and University of Michigan. Its members include Jia Pengyue, majoring in Geographic Information Science and Wang Yi'an, majoring in Computer Science and Technology both from Zhejiang University; Qian Wanying, majoring in Financial Mathematics and Philosophy, and Qu Ge, majoring in Mathematics and Statistics both from the University of Michigan. 

Contemporary Li Shizhen team members

"I liked that we had teams from the U.S., China, and all over the world that worked across a lot of international boundaries to really highlight how data can bring us together globally and help us fight this specific pandemic," Holm said during the interview with XinhuNET.