Elizabeth Qian

von Kármán Instructor at Caltech

In Fall 2022 I will start a new position as Assistant Professor at Georgia Tech in the Schools of Aerospace Engineering and Computational Science and Engineering.

I'm an incoming 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 efforts 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

September 2022: I will give an invited plenary talk at the Symposium on Inverse Problems in Potsdam, Germany (Sept 19--21).

I will also present at the Model Reduction and Surrogate Modeling (MORE) Conference in Berlin (Sept 19--23).

November 2022: I start as Assistant Professor at Georgia Tech on November 1. Looking forward to taking this big step forward in my career!

Recent news

August 2022: Received the Best Presentation Award in the postdoctoral category from the IACM Female Researchers Chapter at the World Congress on Computational Mechanics.

July 2022: New paper proposing new multi-fidelity estimators for global sensitivity analysis is out. When applied to the JW Space Telescope thermal models, our method reduces the computation time from more than 2 months to just 2 days.

June 2022: I received a 2021-2022 ASCIT Teaching Award from the Associated Students of Caltech. Nomination and selection for this award is run entirely by students.

News Archive