Meet a Participant: Priyanka Rao
Applied Mathematician Analyzes Hydro-Climatologic Variables to Predict Fire Occurrence
Priyanka Rao has always enjoyed the intricacies and challenges that come with analytical thinking.
“Mathematics is a subject that I have thoroughly enjoyed throughout my school years,” said Rao. As she entered her collegiate journey, Rao found commonality with peers by participating in several Mathematics Olympiads and conferences. These real-world experiences and collaborations led her to pursue a career in applied mathematics.
As a fourth-year doctoral student studying applied mathematics at Washington State University, Rao is a former participant in the National Science Foundation (NSF) Mathematical Sciences Graduate Internship (MSGI) Program.
The NSF MSGI Program provides research opportunities for mathematical sciences doctoral students, allowing them to participate in internships at Department of Energy and other federal national laboratories. The program seeks to provide hands-on experience for the use of mathematics in a nonacademic setting.
Rao spent the summer of 2021 remotely collaborating with her mentors and other experts to statistically analyze high-resolution weather variables to develop and present a wildfire prediction model. This assisted Priyanka in her understanding of mathematics and statistics in a broader context of natural and environmental sciences.
Under the guidance of her mentors Devendra Amatya, Ph.D., at the U.S. Forest Service Southern Research Station and Sushant Mehan, Ph.D., Research Associate at the University of Wisconsin-Madison, Rao was able to implement extensive data analysis to develop a preliminary assessment model to predict fire occurrence. This model will assess forest managers and researchers for better preparedness in extreme climatic events at the Francis Marion National Forest that includes Santee Experimental Forest in Cordesville, South Carolina.
Additionally, Rao was able to learn how hydrologic variables such as soil moisture, sub-surface water and water table can assist in more accurately assessing potential fire events that typically occur during the summer-fall months. Rao evaluated the prediction model she developed when the water table is deep with lower soil moisture.
Fixing imbalances in the dataset was a new concept for Rao. By gaining knowledge on how to identify appropriate statistical methods for problem-solving, she was able to determine how to fix the skewed data while also correctly interpreting the outcome.
Rao describes NSF MSGI as a “wonderful opportunity to gain first-hand experience of understanding the wide applications of advanced mathematical and statistical techniques.” She further shared that she enjoyed performing the data analysis because of its experimental nature, particularly related to the forest ecosystem and the job creativity involved.
Following her internship with NSF MSGI, Rao was selected to receive the Nancy J. Robertson Endowed Graduate Fellowship in Mathematics on behalf of the Department of Mathematics and Statistics at Washington State University for the 2022-2023 academic year.
Rao wishes to pursue a career as a data scientist after completing her Ph.D. She plans to continue this pursuit in the summer of 2022 as a data science intern at Microsoft.
The NSF MSGI Program is funded by NSF and administered through the U.S. Department of Energy’s (DOE) Oak Ridge Institute for Science and Education (ORISE). ORISE is managed for DOE by ORAU.