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 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
April 2023: I will give an invited plenary at the MASCOT-NUM 2023 conference in Le Croisic, France (April 3-6).
May 2023: I will attend the conference on Nonlinear Model Reduction and Control hosted at Virginia Tech.
March 2023: I virtually presented our work on the cost-accuracy trade-off in learning PDE operators with neural networks in the Johns Hopkins University postdoc seminar in the Department of Applied Mathematics and Statistics on March 14.
February 2023: I presented our work on multifidelity global sensitivity analysis for the JW Space Telescope at SIAM CSE 23 in Amsterdam (Feb 26 - Mar 3). GT CSE Communications Officer Bryant Wine wrote a piece highlighting this work and other GT CSE contributions at the conference.