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 2025: I will give an invited talk on February 27 at the Scientific Machine Learning Workshop organized in conjunction with the 2025 Energy HPC Conference hosted by the Ken Kennedy Institute at Rice University.
March 2025: I will be at SIAM CSE 2025 in Fort Worth on Monday March 3 (and possibly Tuesday) presenting our multifidelity linear regression work.
Recent news
December 2024: New paper on Inference-oriented model reduction for quadratic dynamical systems has been published in Proceedings in Applied Mathematics and Mechanics. Fulbright visiting PhD student Josie König has led this collaboration with her home institution, the University of Potsdam.
November 2024: Our work on Multifidelity linear regression for scientific machine learning from scarce data has been published in Foundations of Data Science.