To strengthen the connection between the statistical community and National Science Foundation, we continue the series introduced in the May 2023 issue that poses questions to NSF program officers and awardees. If you have questions or comments for the program officers, send them to ASA Director of Science Policy Steve Pierson.

NSF Statistics Program Directors

Yulia Gel, Edsel Peña, Yong Zeng, and Jun Zhu collectively responded to the following questions. Zeng, from the University of Missouri-Kansas City, became a permanent program director, and Zhu, from the University of Wisconsin-Madison, became a rotator program director of the Division of Mathematical Sciences in the NSF Directorate for Physical and Mathematical Sciences in 2022. They joined Gel from The University of Texas at Dallas and Peña from the University of South Carolina-Columbia, who are in their second and third years, respectively, as rotator program directors of the statistics program. Zeng served in the Division of Mathematical Sciences from 2015–2018 and 2019–2021.

How do you become an NSF reviewer/panelist?
If you are interested in serving on an NSF statistics panel, send an email to the appropriate program officers in the statistics program and attach your CV or biographical sketch. The statistics program officers keep a database of review volunteers.

Do I need to hold an NSF grant to become a panelist?
You do not need to have an NSF grant to become a panelist. Postdoctoral fellows may also serve on panels. We strive to enhance all aspects of diversity in NSF panels, including diversity of career stages.

NSF Awardees

Gang Li, Hua Zhou, and Jin Zhou of the University of California at Los Angeles collaborated to apply for and receive their first funding from the Division of Information and Intelligent Systems in the NSF Directorate for Computer and Information Science and Engineering. Their project focused on linking individual continuous glucose levels and longitudinally measured risk factors to adverse diabetes-related events.

Gang Li, Hua Zhou, and Jin Zhou have prior experience applying for NSF grants, but this was their first time applying for grants sponsored through the Division of Information and Intelligent Systems.

How will the funding be used?
Our primary collaborator for this grant is Peter Reaven from Phoenix VA Hospital, and our industry partner is Dexcom Inc. The total funding amount is $1.2 million. Besides principal investigator efforts, computation, and publication costs, the funding will be spent on students and postdocs.

Summarize the goal of what the proposal will accomplish.
Our proposal aims to address the need for scalable methods and software to make use of modern sensor and multi-modal clinical data to link individual continuous glucose levels and longitudinally measured risk factors to adverse diabetes-related events. The proposal aims to develop novel statistical methods, computational algorithms, and user-friendly software that are scalable and adaptable to different data types. The focus is on algorithm development with statistical guarantees to answer scientific and clinical questions. The proposal also emphasizes education and outreach activities to expose a diverse set of students to state-of-the-art data science techniques for smart health.

If an NSF non-DMS entity partially or fully funded the award, can you describe your approach to that entity?
Our grant responds to the NSF request for application “Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science (SCH),” sponsored by the Division of Information and Intelligent Systems. We recommend strictly adhering to the guidelines of the call, including incorporating the required evaluation plan and covering all four specific areas with the exact titles requested by Smart and Connected Health.

Our proposal not only emphasizes statistical theory but also showcases the computational aspects of the grant and provides evidence of the practical use of the tools we aim to develop. We clearly state the health care problems our proposal aims to address, and we recognize an interdisciplinary team with strong working relationships is critical for success.

What advice do you have for others applying for NSF funding?
Read the guidelines carefully. Before you start your application, make sure you read the NSF guidelines carefully and understand the requirements and expectations of the program you are applying for.

Be clear and concise. Make sure your proposal is well-organized, easy to follow, and clearly states the significance and potential impact of your research. Use simple language and avoid technical jargon as much as possible.

Highlight broader impacts. The NSF places strong emphasis on the broader impacts of research. Make sure to clearly state the potential broader impacts of your research on society, education, and outreach.

Collaborate with colleagues. Consider collaborating with colleagues not only in your field but from other disciplines to strengthen your proposal and demonstrate the broader impact of your research.

Follow up. After submitting your proposal, don’t hesitate to follow up with the NSF program officer if you have any questions or concerns. They can provide valuable insights and help you navigate the NSF review process.