Data competitions provide invaluable opportunities for Virginia Tech undergraduates

They say practice makes perfect.

For aspiring data scientists, data competitions — like the ones Christian Lucero, collegiate associate professor in the Department of Statistics, has run at Virginia Tech for nearly a decade — help students achieve this “practice.”

Instead of working with classroom data sets and questions that have answers straight out of a textbook, data competitions provide students with the opportunity to work on open-ended real-world problems.

Virginia Tech recently hosted its ninth-straight American Statistical Association (ASA) DataFest event.

The event, held April 12-14, was one of more than 60 ASA DataFest competitions that took place this spring with over 100 colleges and universities across the United States and beyond taking part in the contests.

The ASA DataFest, founded in 2011, is a celebration of data in which teams of undergraduates work around the clock to find and share meaning in a large, rich, and complex data set.

Each year, the American Statistical Association supplies DataFest organizers with an official data set provided by an outside source. To ensure fairness between events, the data provider’s identity remains embargoed until the final ASA DataFest competition is held in early May.

Data for the 2025 ASA DataFest was provided by Savills, an international commercial real estate firm that helps businesses find locations to lease their offices. The challenge for this year’s competitors was to inform Savills of notable trends or microtrends in the commercial real estate market that could be used to advise clients on where, when, whether, and how to locate their offices.

Over 130 Virginia Tech students registered for this year’s data competition, which was open to undergraduates in any major. Participants were given the weekend to work on their projects before submitting video presentations on Sunday. The top six teams, based on initial scoring by the event judges, then provided live presentations on Monday to determine the final award winners.

Three prizes were awarded at the conclusion of the event: Best Visualizations, Best Methodology, and Best Overall Presentation.

• Best Visualizations: Team 404 made up of Husaina Badani, Sophia Chukka, Akshat Kumbhat, Aditya Singh, and Kareena Singh
• Best Methodology: The RIZLA made up of Zainub Farooq, Antonio Pinto Guardia, Lidia Pinkevich, Ian Russell, and Riley Spoenlein
• Best Overall Presentation — the grand champion: Query Queens made up of Namrata Hari, Hailey Patel, and Sarayu Pulipati

Fall competition

Students don’t have to wait until spring to flex their problem-solving data skills. Each year, the Computational Modeling and Data Analytics Club hosts a Fall Data Competition, also open to Virginia Tech undergraduates of any major.

The Fall Data Competition has a setup like that of the ASA DataFest, with equivalent timelines and team sizes. However, in the fall, there are two competition tracks — beginner and advanced — and Lucero designs the challenges himself, rather than using datasets and problems provided by a national organization.

For the fall 2024 competition, students on the beginner track were provided with data sets focusing on three different topics — waste data, ecological health, and crops — and tasked with coming up with a question that could be answered using one of these sets.

Meanwhile, teams competing on the advanced track were asked to investigate a research question in one of two areas — inequality, discrimination, and sexual violence or “sunshine and puppies,” highlighting something positive in the world. However, these students had to find their own data sets related to the proposed questions.

Prizes for Best Visuals, Best Methodology, and Best Overall Presentation were awarded in each track.

The winning teams included:

Beginner Track

• Best Visualizations: Bernoulli’s Ballers made up of Vishana Baskaran, Morgan Bradley, Ashley Powell, and Samika Reddy
• Best Methodology: Statistical Sophomores made up of Namrata Hari, Hailey Patel, Sarayu Pulipati, Saina Shibili, and Sarah Skaggs
• Best Overall Presentation, the grand champion: Data Dawgs made up of Jocelyn Bliton, Baker Dean, and Margaret Smith

Advanced Track

• Best Visualizations: The Rizziduals made up of Grant Marsh, Andrew Phan, and Daniel Quimbayo-Cipric
• Best Methodology: Thread Masters made up of Liam Curtis, Colin Lange, Rowan Martnishn, Zach Miller, and Nate Williams
• Best Overall Presentation, the grand champion: Hokie Hackers made up of Nami Jain, Drew Keely, Devanshu Khadka, and Ted Li

A bonus for the 2024 Fall Data Competition was the participation of a corporate sponsor, Accenture Federal Services, which provided prizes to the winning team. Renzo Silva, a 2013 graduate from the Pamplin College of Business, was joined by a pair of 2024 computational modeling and data analytics alumni who currently work for Accenture and served as judges for the event. According to Silva, Accenture — which has been project partner for the computational modeling and data analytics program’s capstone course — has been actively looking to increase engagement on campus.

“Accenture Hokies are a big and proud group and community,” said Silva about why the company sponsoring the event. “There’s the aspect of, 'Yes, we want to be back in the community,' but really, it's, ‘How do we help build the next generation of Hokies?’ Part of it is encouraging events like this where they get to try out new skills and maybe even challenge themselves.”