Data Science Student Wins Poster Competition | University of Arkansas

2022-06-10 21:14:00 By : Ms. Yolanda Bai

Abby Willard and her winning poster: "NSF EPSCoR DART Education Theme Case Study Project"

Researchers involved in the Arkansas NSF EPSCoR DART program met recently at the Data Analytics that are Robust and Trusted All Hands Meeting and Student Poster Competition in Little Rock. Abby Willard, a rising data science honors junior, won first place in the poster competition at the conference.

Willard's project, which included help from her faculty adviser, Karl Schubert, and her staff adviser, Lee Shoultz, involved creating data science case studies for other colleges and universities in the "Data Science for Arkansas (DS4A)" ecosystem to help kick-start their courses and programs. This project is important and insightful as the Data Science Program at the U of A, which launched in the fall of 2020, is the first of its kind in the state of Arkansas. Willard's award-winning poster, titled "NSF EPSCoR PI Team Case Study Project," earned her a prize of $1,000 to be used toward attending a future conference of her choice.

Karl Schubert, associate director of the Data Science Program at the U of A, said, "I am very proud of Abby and her contribution to our state-wide data science ecosystem, 'Data Science for Arkansas,' as recognized by her winning poster. Her work is helping us and our two-year and four-year data science program partners with sample case studies with real-world data and real-world problems."

About DART: In 2020, the Arkansas Economic Development Commission's Division of Science and Technology, in partnership with the U of A and eight other colleges and universities, was awarded a $20 million grant from the National Science Foundation's (NSF) Established Program to Stimulate Competitive Research (EPSCoR). The grant is matched by $4 million from the state. As a result, researchers established a program titled "Data Analytics That Are Robust and Trusted," or DART. DART is designed to address fundamental barriers to practical application and acceptance of modern data analytics, learning and prediction, any one of which could derail or impede its full development and contributions. DART will also establish a statewide data science educational ecosystem by defining a combination of model programs, degrees, pedagogy and curriculum; providing resources and training for K20 educators; providing educational opportunities inside and outside the classroom for K20 students; and ensuring broad participation to impact the state's pipeline of data science skilled workers.

Karl D. Schubert, professor of practice and associate director Data Science 479-575-2264, schubert@uark.edu

Lee Shoultz, program manager Data Science 479-575-5469, eshoultz@uark.edu

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