Elizabeth Qian
Assistant Professor at Georgia Tech
Assistant Professor at Georgia Tech
I am serving as a guest editor for a special issue of Structural and Multidisciplinary Optimization (SMO) on "Reduced Order Modeling, Generative AI, and SciML in Digital Twins". Submissions are currently being accepted until October 31 (deadline extended from July 31).
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.
August 2025: I will present progress on our project on developing efficient reduced models for inference and estimation problems at the Air Force Office of Scientific Research (AFOSR) Computational Mathematics program review, August 18 - 22 (my presentation will likely be online).
July 2025: I'm pleased to be the recipient of an NSF CAREER award from the program on Engineering Design and Systems Engineering (EDSE). This award will support my group's research developing machine learning methods that learn from multifidelity data.
Two new preprints are available on arXiv:
(1) Dimension and model reduction approaches for linear Bayesian inverse problems with rank-deficient prior covariances, led by Josie König, who visited ACE Group in Fall 2025 as a Fulbright visiting student.
(2) An ensemble Kalman approach to randomized maximum likelihood estimation, led by GT PhD student Pavlos Stavrinides.