Elizabeth Qian

Elizabeth Qian is a tenure-track Assistant Professor at Georgia Tech with joint appointments in the Schools of Aerospace Engineering and Computational Science and Engineering. She holds a visiting Hans Fischer Fellowship at the Technical University of Munich Institute for Advanced Study (TUM-IAS) since 2023. Her research develops computational methods for scientific machine learning, model reduction, and multifidelity approaches to accelerate engineering decision-making.

• Education: PhD (2021), SM (2017), and SB (2014) in Aerospace Engineering from MIT

Her work focuses on enabling efficient simulations for complex systems through model reduction, scientific machine learning, and multifidelity methods. Recent publications address Bayesian inverse problems, neural operator learning trade-offs, and ensemble Kalman methods.

Scientific awards include the 2025 NSF CAREER Award, 2024 AFOSR YIP Award, 2023 TUM-IAS Fellowship, 2022 SIAM Student Paper Prize, and 2014 Hertz/NSF/Fulbright fellowships. She mentors GT PhD researchers and contributes to diversity initiatives in engineering communities.