Data Challenge 2019 Awards

Grand Prize

Team DC19028
Nisha Dayananda | Prathima Devanath | Sandeep Raju | Prashant Rathod
Dataset: Real-time Train Prediction
Supplied by: Washington Metropolitan Area Transit Authority

Best Community Integration

Team Dc19017
Luc d’Hauthuille | Yung Tzu Huang | Ruthwik Kuppachi | Ling Shu Kung
Dataset: mBike Bikeshare
Supplied by: City of College Park

Most Innovative Project

Team DC19016
Yushuang Chen | Wenyan Tuo | Can Yang
Dataset: Trump Dataset
Supplied by: FactSquared

Highest Quality Project

Team DC19047
Sanaz Aliari | Moein Eshfagh | Longsheng Yin | Yaqian Zhang
Dataset: mBike Bikeshare
Supplied by: City of College Park

Best Expression of Results

Team DC19006
Matthew Chou | Yasmin Ibrahim | Kanika Taneja
Dataset: Police Crime Statistic Analysis
Supplied by: City of New Carrollton

Best Team Presentation

Team DC19051
Olivia Isaacs | K. Sarah Ostrach | Natalie Salive
Dataset: Legacy of Slavery in Maryland
Supplied by: University of Maryland Digital Curation Innovation Center

Outstanding Undergraduate Team

Team DC19005
Erick Herrera | Nathan Kwon | Jonah Lynn Rivera
Dataset:  Signal Detection Exercise
Supplied by: UMD National Consortium for the Study of Terrorism and Responses to Terrorism

People’s Choice Award

Team DC19003
Shruti Hegde | Vyjayanthi Kamath | Himanshi Manglunia
Dataset: Police Crime Statistic Analysis
Supplied by: City of New Carrollton

Hosted by:


What is Data Challenge?

Data Challenge is an annual week-long data exploration event at the University of Maryland hosted by The College of Information Studies and The School of Architecture, Planning and Preservation, Maryland’s School of the Built Environment (MAPP)

During the week, UMD students will gain analytical experience by solving challenging problems exploring novel datasets, build technical aptitude integrating datasets to create multidisciplinary knowledge, and obtain real-world team-building experience.

All UMD students are invited to participate.

Students will choose from the sponsor provided datasets to work with for the week, and will be encouraged to use additional 3rd party services, APIs, open source projects libraries, and frameworks to create and answer a unique question about their chosen dataset. This week long distributed format allows students sufficient time for evaluation, question formation, dataset integration, analysis, and results preparation.

In addition, the students will have an opportunity to participate in sponsor’s tech talks, network with a variety of organizations, and learn about future connections with the organizations.

No matter what major the students are from, they can partner up for a social cause, show off their skills and make their contribution to creating something innovative!


Data Challenge Event February 23 – March 2, 2019

Challenge Kickoff | February 23, 2019 9:00am – 5:00pm

Teams meet with mentors on campus to discuss ideas, frame the research question, start the analysis work and set expectations for the week.

Research Showcase and Judging Day | March 2, 2019 9:00am – 5:00pm

Teams present the outcomes of their analysis to the Data Challenge Judges, data enthusiasts, friends, family, and anyone who is interested to see the amazing work the students have created during the week.