Meet a Participant: Sara Nasab
Interdisciplinary student discovers passion of mathematics
If you had met Sara Nasab as an undergraduate student, you may not have guessed that she would one day pursue a doctoral degree in mathematics. Interested in nearly every subject, Nasab completed pre-medical school requirements, majored in Spanish and conducted a senior thesis in art history during her college years.
Despite her extensive interdisciplinary background, Nasab felt she was missing a problem-solving element in her education. Recalling her love for math in high school, Nasab decided to pursue a master’s degree in mathematics, where she rediscovered her passion and solidified her career path.
Now a doctoral student of applied mathematics at the University of California, Santa Cruz, Nasab has sought to expand her academic repertoire even further with hands-on experience outside of academia. Discovering the perfect opportunity, Nasab applied to the National Science Foundation’s (NSF) Mathematical Sciences Graduate Internship (MSGI) Program.
The NSF MSGI program offers research opportunities for mathematical sciences doctoral students to participate in internships at national laboratories, industries and other facilities. NSF MSGI seeks to provide hands-on experience for the use of mathematics in a nonacademic setting.
Nasab participated in a project at Lawrence Berkeley National Laboratory (LBNL), Berkeley, California, in the Center for Computational Sciences and Engineering Group. There, Nasab began to conduct research in cloud and related particle dynamics under the mentorship of Andrew Myers, Ph.D.
For the project, Nasab sought to include point particles using LBNL’s AMReX particle libraries to her already existing fluid code. Incorporating such a fine detail into a model, however, is not an easy task. The majority of Nasab’s 10-week internship was spent building this particle-fluid code, which involved intensive programming. Nevertheless by the end of the program, Nasab and her mentor were able to successfully incorporate the particles, creating the basis of a full hybrid particle-fluid code.
Nasab seeks to understand the physical processes that droplets experience while in a cloud. With the particle-fluid code completed, the next steps are to add processes such as condensational growth and droplet-droplet collisions.
The need for cloud modeling is vital for weather prediction. Weather forecasts can be difficult to create accurately because of a limited understanding of rain formation. By studying how droplets grow and form in clouds on a small scale, forecasters can improve their knowledge of larger cloud processes and dynamics, such as rain formation and precipitation efficiency. Nasab’s research findings represent a significant step toward improving accuracy of cloud models, leading to improved forecasting tools.
Nasab recognized that she has had a relatively nontraditional background compared to other NSF MSGI interns. She credits her interdisciplinary background as part of her success as well as affirmation of her passion for science, technology, engineering and mathematics (STEM). Likewise, the NSF MSGI Program has had a significant impact on Nasab and her career goals.
“This was one of the most eye-opening experiences in my Ph.D. career,” Nasab said. “It gave me a glimpse of what day-to-day life is like at a research lab, along with widening my circle of collaborative professionals.”
Nasab returned to UC Santa Cruz to continue her doctoral degree. She and her mentor plan to publish the results of their research. She hopes to continue the collaborative relationships she gained at LBNL. “I enjoyed [the program] so much that I hope to return next year, and ultimately continue my career here [LBNL] after I graduate,” Nasab said.
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.