Lindner PhD student's paper wins two industry awards
Zewei Lin is a fourth-year doctoral student in business analytics
The New England Statistical Society and the Symposium on Data Science and Statistics recently bestowed awards upon Zewei Lin, a fourth-year doctoral student at the Carl H. Lindner College of Business.
Lin, pursuing a PhD in business analytics in the department of operations, business analytics, and information systems (OBAIS), recently won the New England Statistical Society’s (NESS) Student Poster Award and the Symposium on Data Science and Statistics’ (SDSS) Early-Career Student Award on the strength of his research paper, “Model diagnostics of discrete data regression: a unifying framework using functional residuals.”
Lin was one of five winners of the Student Poster Award. Lin’s supervisor at Lindner, OBAIS Associate Professor Dungang Liu, PhD, noted that Lin was the lone Student Poster award winner stationed outside of the Northeast, as the other victors hailed from Harvard University (two), the Massachusetts Institute of Technology, and the University of Rhode Island.
Liu was also on hand for Lin’s SDSS presentation.
“The room was full, and I could tell that the audience reacted very positively to his presentation,” Liu said. “I think Zewei truly exemplifies how Lindner PhD students can make an impact out of the Midwest.”
Lin’s primary research interests lie at the intersection of analytics of discrete data and applications to information systems and insurance. A 2019 graduate of Renmin University of China, Lin has already published a research paper in the British Journal of Mathematical and Statistical Psychology.
“Before joining UC, I was a college student in statistics and was attracted by research in application fields,” Lin said. “I made use of my summer holiday to do research in the lab at the University of Wisconsin-Madison. This experience confirmed the academic goal of my career and helped me make the decision to join the business analytics PhD program.”
Featured image: Zewei Lin presents at the Symposium on Data Science and Statistics. Photo courtesy of Zewei Lin.
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