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. I also currently hold a visiting appointment as a Hans Fischer Fellow at the Technical University of Munich. 

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 teaching contributions have previously been recognized with departmental and division-wide DEI awards, as well as an institute-wide teaching award.

Upcoming talks & activities

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 (part I, part II, part III). I will also present our work on balanced truncation for ensemble Kalman inversion in a minisymposium on uncertainty quantification for digital twins

March 2024: Abstracts are due March 1 for presentations at MORe2024 in San Diego (September 9-13, 2024). I am serving on the scientific committee for this iteration of this excellent workshop on model reduction and surrogate modeling.

April 2024: I will give the CODES Seminar at Emory University on April 4. 

Recent news

January 2024: Welcome to two new undergraduate researchers, Holden Rohrer and Ben Zabriskie!

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

December 2023: My proposal to Air Force Office of Scientific Research (AFOSR) Young Investigator Program (YIP) was selected for funding. The grant will support research on model reduction methods for inference problems. More info in the AFOSR press release.

News Archive