Elizabeth Qian

Assistant Professor at Georgia Tech

I'm an Assistant Professor at Georgia Tech in the Schools of Aerospace Engineering and Computational Science and Engineering. My research develops mathematical and computational methods that enable engineers to make better design decisions faster. My specialties are model reduction, data-driven modeling, scientific machine learning, and multi-fidelity methods. You can learn more on my research page.

Prior to joining the faculty at Georgia Tech, I held a von Kármán Instructorship at Caltech in the Department of Computing + Mathematical Sciences. I received my SB, SM, and PhD degrees from the MIT Department of Aeronautics & Astronautics. My research has been funded in parts by a Fulbright student grant, an NSF Graduate Research Fellowship and a Hertz Foundation Fellowship

I am excited about mentoring and teaching the next generation of aerospace engineers and computational scientists, and I work to make my professional communities more equitable, diverse, and inclusive for generations to come. My service and mentoring contributions at Caltech were recognized with the departmental and division-wide DEI awards, and I also received an institute-wide teaching award from the Associated Students of Caltech (ASCIT).

Upcoming talks & activities

January 2024: PhD student Tomoki Koike will present a paper at AIAA SciTech in session MDO-08: Metamodeling, Reduced Order Models, and Approximation Methods I. I will chair this session as well as MDO-09: Machine Learning and Optimization.

February 2024: I will attend the SIAM Conference on Uncertainty Quantification held in Trieste, Italy from February 27 to March 1. Peng Chen and I are co-organizing a three-part minisymposium on Scalable algorithms for Bayesian inverse problems. I will also present our work on balanced truncation for ensemble Kalman inversion in a minisymposium on uncertainty quantification for digital twins. 

Recent news

October 2023: I am a co-PI on the ROME: Reduced Modeling with Extreme Data project, a DOE-funded multi-institution collaboration that will develop new model learning methods for Energy Earthshot applications. More information in the DOE press release and the GT AE news story.

September 2023: I have been awarded a Hans Fischer Fellowship by the Institute for Advanced Study at the Technical University of Munich (TUM). The fellowship will support a research collaboration with TUM researchers on reduced modeling for structural reliability analysis.

News Archive