Mines News

Release Date Friday, April 14, 2023

Mines Data Science Team Captures Top Honors at Regional Competition in Minneapolis

South Dakota Mines students on the winning data science team at this year’s MinneMUDAC competition include math and computer science majors Jacob James and Colton Snyder, math major Trevor Krason and computer science major Karissa Schipke. These students are part of the data science club (referred to as the Data Miners) at Mines.

A team of South Dakota Mines mathematics and computer science students captured top honors at the MinneMUDAC data science competition held at Target Field in Minneapolis, Minn. Mines took home a second place honorable mention and was one of three teams recognized among the 28 universities in the undergraduate division.

Mines was among the smallest schools at the event, but the institution has established a history of doing very well at this competition with a number of top scoring teams and individuals during the last five years. This year the Mines undergraduate team finished above other schools like Syracuse, University of Wisconsin Madison and the University of Minnesota College of Science and Engineering.

Each year the MinneMUDAC competition offers a new challenge. This year, event organizers, MinneAnalytics, teamed up with the Minnesota Twins to develop a program that could predict gate attendance for home games during the 2023 season. Student teams were required to gain an understanding of how various factors influence attendance at Major League Baseball (MLB) games and then tasked to consider the Minnesota Twins and MLB as their clients.

“Our students did a very, very good job at analyzing the data and forecasting future MLB attendance,” says Kyle Caudle, Ph.D., a professor of mathematics at Mines and one of the team’s advisors. “One of the unique ideas the team came up with was to use an ensemble method (a way to aggregate multiple models to provide a more accurate prediction), they were the only team to consider this approach,” says Randy Hoover, Ph.D., a professor of Electrical Engineering and Computer Science and the other team advisor. Sherwyn Braganza, a Ph.D. student in Data Science and Engineering at Mines, also mentored the team this semester and helped guide some of the data visualization.

A secondary prize will be awarded to the team with the predictions that come closest to reality in the fall at the conclusion of the baseball season. The winning team gets the chance to work with the Minnesota Twins to have their version of the software developed for use.

This year’s MinneMUDAC competition students include math and computer science majors Jacob James and Colton Snyder, math major Trevor Krason and computer science major Karissa Schipke.

Mines offers a number of degrees and specializations that allow graduates to quickly become industry leaders in highly sought fields of data analytics. These include, computer science, computer engineering with an Artificial Intelligence and Machine Learning specialization, and mathematics with specialization in data science alongside Ph.D. graduate programs in data science and engineering.



About South Dakota Mines  

Founded in 1885, South Dakota Mines is one of the nation’s leading engineering, science and technology universities. South Dakota Mines offers bachelor’s, master’s and doctoral degrees and a best-in-class education at an affordable price. The university enrolls 2,493 students with an average class size of 24. The South Dakota Mines placement rate for graduates is 98 percent, with an average starting salary of more than $70,036. For these reasons  South Dakota Mines is ranked among the best engineering schools in the country for return on investment. Find us online at www.sdsmt.edu and on FacebookTwitter, LinkedInInstagram, and Snapchat.

Contact: Mike Ray, 605-394-6082, mike.ray@sdsmt.edu