Pilot Research Award Program Launched with Four Faculty Recipients

The School of Data Science has launched a new Pilot Research Award Program designed to accelerate early-stage, high-potential research by providing targeted support for faculty projects in their initial phases. The award offers short-term funding that can be used for graduate or postdoctoral research assistance, data collection, computing resources, travel for scholarly collaboration, or other project needs. This award will help researchers rapidly test new ideas, generate preliminary results, strengthen future grant proposals, and foster collaboration across the School and the University.

The School is pleased to announce the inaugural recipients of this new program:

• Peter Beling
• Natalie Kupperman
• Nur Yildirim
• Chirag Agarwal and Nur Yildirim (joint award)

"The irony is that the key to a successful grant application is to have as much of the work done before you get the grant," said Phil Bourne, founding dean of the UVA School of Data Science. "At the least, this means an innovative research plan, and preliminary high-quality data. These grants are designed to help with this."

Building on Dean Bourne’s emphasis on nurturing early-career scholars and supporting emerging research topics prioritized by federal funding agencies, this inaugural cohort reflects the very purpose of the Pilot Research Award Program. Their projects demonstrate how targeted support at a formative stage can spark new lines of inquiry, expand the frontiers of data science research, and strengthen the foundation for discoveries that will shape the School’s next chapter.  

Faculty Recipients 

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Chirag Agarwal 
Assistant Professor of Data Science

Chirag Agarwal leads the Aikyam Lab, where he develops trustworthy and robust machine-learning methods. His work spans biomedical and health applications, environmental and climate science, and ethical and social considerations in AI. His collaborative award with Nur Yildirim recognizes the synergy between human-centered AI and methodological innovation.

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Peter Beling 
Professor of Data Science

Peter Beling’s research explores generative AI and mission-aligned, resilient machine-learning systems, with a strong emphasis on applications in national security and strategic decision-making. His work through the National Security Data and Policy Institute focuses on building AI systems that are reliable, transparent, and aligned with organizational and societal priorities.

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Natalie Kupperman 
Assistant Professor of Data Science

Natalie Kupperman specializes in sports science, athlete monitoring, and data-driven health insights. A certified athletic trainer, she integrates machine learning with biometric and performance data to advance evidence-based approaches to human health, movement, and injury prevention.

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Nur Yildirim 
Assistant Professor of Data Science

Nur Yildirim’s research focuses on human-centered and participatory approaches to the AI lifecycle. She studies how stakeholders can be meaningfully involved in the design, evaluation, and deployment of AI systems, with the goal of advancing technologies that are equitable, transparent, and aligned with social values.