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May 29, 2025

Spartan engineer awarded prestigious Frontera Computational Science Fellowship

Firsts for both the university and the state

Sunia Tanweer of Michigan State University (MSU) was awarded the prestigious Frontera Computational Science Fellowship. She is a third-year dual Ph.D. candidate in the Department of Mechanical Engineering (ME) and the Department of Computational Mathematics, Sciences and Engineering (CMSE) in the College of Engineering.

Woman standing outside, grass and trees in the background, wearing a hijab and smiling at the camera
Sunia Tanweer

Tanweer, who works in CMSE’s Khasawneh Lab, is the first MSU student to win a Frontera Computational Science Fellowship and one of the first recipients from an academic institution in the state of Michigan since the inception of the fellowship in 2020.

"I’m honored to receive the Frontera Fellowship and excited to use its computational power to better predict instability in aircraft systems." said Tanweer.

This NSF-funded fellowship is awarded annually to three to five advanced Ph.D. students from across the United States. It provides for a yearlong collaboration with experts at the Texas Advanced Computing Center (TACC). It also includes time to conduct research on Frontera, the fastest supercomputer in the United States, along with a stipend, tuition allowance, and travel funding for visiting TACC and presenting at professional meetings.

“Congratulations to Sunia on this groundbreaking achievement,” said Minami Yoda, chair of ME. “We are proud of this national recognition for our graduate student.”

Ed Brown, chair of CMSE, seconded that sentiment. “It’s exciting to see how this fellowship will enrich both Sunia’s research and computational science in general.”

“My goal is to build an algorithmic pipeline for automated prediction and prevention of dangerous stall events - ultimately contributing to safer skies,” Tanweer explained.

Unintentional stalls in airplanes are deadly, resulting in fatalities almost 50 percent more often than non-stall accidents. Although pilots are taught to recognize, avoid, and recover from stalls early in-flight training, they still account for almost a quarter of fatal accidents.

Tanweer’s recent work allows data-driven detection of such phenomenon in real time as well as through computational modeling in advance.

Learn more about the Frontera Fellowship.

Written by Judi Melena Smelser

MSU College of Engineering  Media and Public Relations page

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