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Arjun Arora, Hong Li and Ran Zhang in front of Las Vegas sign

Analytics Students Place at International Competition

BY DIANA JONES

April 05, 2017

A team of three graduate students in Drexel LeBow’s MS in Business Analytics program was awarded fifth place recognition in an operations research and analytics competition of more than 200 competing student teams from around the world.

Arjun Arora, Hong Li and Ran Zhang accepted the honor during the Institute for Operations Research and the Management Sciences (INFORMS) Analytics conference in Las Vegas, Nev.

Eight teams from locations around the world – including Turkey, Singapore, the U.K. and Belgium – were selected as finalists in the inaugural INFORMS Operations Research and Analytics Student Team Competition. Drexel University was one of three U.S. institutions to be recognized in the final round of the competition.

Teams were given a real business problem and data sets from Syngenta, a global seed biotechnology company. Students were tasked with using an operations research and analytics approach to discover why strains of soybean varieties selected and bred for commercialization were under-performing.

Arora, Li and Zhang were selected as finalists based on a written submission of their analytics process, from framing the problem to methodology selection, data use, model building and quantitative analysis. As finalists, the team of students was invited to Las Vegas to present their solutions to a judging panel of industry and academic professionals. Their recommendations earned them a fifth place ranking out of 200 competing teams and a $1,000 prize.

The students worked on the challenge for several months with guidance, oversight and support from their faculty advisor, Chuanren Liu, PhD, Assistant Professor, Decision Sciences and MIS.

“The biggest challenge for us was interpreting how to use the information we were given,” said Arora. “Our courses prepared us with critical thinking experience, storytelling knowledge and the ability to build regression models, so this competition was a good opportunity to use those skills and learn more about developing solutions using historical data.”

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