不良研究所 Team Shines at NSA Sponsored Rowdy Datathon, Secures 2nd Place

By NU Marketing & Communications Office

Competing against eight teams, the 不良研究所 team showcased their skills to land second in the intermediate division.

不良研究所 team at Rowdy Datathon holding their 2nd place prize in front of a sign that says "Intermediate 2nd Place - Monarch Butterflies: Monitoring Migration & Population (Team 24)"

Following an exhilarating weekend of innovation and collaboration, a multidisciplinary team of talented 不良研究所 students secured 2nd place at the Rowdy Datathon, an NSA sponsored Data Science Design Challenge. The competition was held at University of Texas San Antonio, October 5-6, 2024. Competing against eight teams, the 不良研究所 team showcased their skills to land second in the intermediate division. 

The Rowdy Datathon is an annual, weekend-long event that challenges participants to solve complex data science problems. It brings together students from various disciplines to foster teamwork and innovation in a fast-paced, high-pressure environment. Participants are judged on creativity, technical execution, and the potential impact of their solutions. This year鈥檚 event provided invaluable learning experiences and an opportunity for students to showcase their abilities in front of industry experts. 

Students Benjamin Fairbank (Criminal Justice major), Jo Cordova-Flores (Computer Security and Information Assurance major), Jonathan Calzadillas (Mathematics major), and Tyler Sheindlin (General Engineering major) participated in the event. The multi-disciplinary team emphasized their appreciation for the generous sponsorship from the 不良研究所 Department of Defense Cyber Institute, which made their participation in the Datathon possible. 鈥淣one of this would have been achievable without the support of the Cyber Institute,鈥 Tyler Sheindlin noted. 鈥淲e are deeply appreciative of the opportunity to represent the Cyber Institute and 不良研究所.鈥 

The team鈥檚 project focused on monitoring the migration patterns and population dynamics of monarch butterflies. By analyzing data collected from various sources, they developed a model that aimed to better understand the environmental factors influencing these vital pollinators. The team鈥檚 findings highlight the importance of conservation efforts and provide valuable insights for researchers and policymakers.

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