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A team of the three graduating seniors placed in the top five in the nation for the COMAP International Math Modeling Competition.

This is the first year that a department-sponsored, all-Business Analytics Technology (BAT) student team from �԰����� participated, receiving the distinction of “meritorious winner.” Another  team of �԰����� math students received “successful participant" honors. 

Finishing among the top five in the nation and within the top six percent globally represents “�԰�����'s best run ever,” according to Jorge Colazo, Ph.D., associate professor and chair of the Department of Finance and Decision Sciences, who originally encouraged the team to compete. “In fact, we beat Duke, Brown, UNC-Chapel Hill, Michigan State, Case Western, Ohio State, UCLA, Illinois Urbana-Champaign, and Peking University, which is the second-ranked university in China.”

The winning team consisted of Kit Alderson ’20, Eric Liang ’20, and Alex Motter ’20, all BAT majors. None of them had taken any specific math modeling classes, but each expressed that they felt confident in their skills thanks to their work in the BAT program and the help of professors like Colazo and other BAT faculty, as well as Kara Larkan-Skinner, Ph.D., executive director for Institutional Research and Effectiveness at �԰�����. 

The COMAP competition is a chance for students to solve a real-world math problem and obtain international recognition. The team’s task involved identifying insights and developing metrics to inform things like design, marketing, and timing of participation for a company that wanted to sell three products online. Three datasets containing past online purchase information involving similar products were provided to support their mathematical models. The team used text-based analysis techniques, time series analyses, and clustering, blending them into unified models that produced clever recommendations and visualizations.

“The problem asked us to design a data-driven product strategy for a company planning to release three new products on an e-commerce platform. This presented many unique challenges, not the least of which being that the data we modeled came from Amazon reviews that contain slang, spelling errors, and tone like sarcasm that doesn't translate easily over machine learning algorithms,” says Motter. 

What sets our solution apart from some of the other competitors, and why I feel we received such high marks, is that our background for BAT provides both the mathematical modeling toolkit and the businesses school of thought.”

All three competitors recently graduated from the University. Like many others right now, Motter’s plans for after �԰����� have been disrupted because of the pandemic. He is currently planning out what will come next. Since graduating, Liang and Alderson have accepted positions putting what they’ve learned at �԰����� into practice. Liang will be joining Epic in Wisconsin as a project manager working on its analytics platform, and Alderson will be working at USAA in Plano, Texas, as a data engineer III.