PhD Candidate, MIT Center for Computational Engineering
I am a final-year PhD student in the Center for Computational Engineering and the Department of Aeronautics & Astronautics at MIT. My advisor is Professor Karen Willcox, and my research interests are in data-driven model reduction and multifidelity methods for uncertainty quantification and optimization.
I received my SB in Aerospace Engineering from MIT in 2014. Prior to beginning graduate studies, I was awarded a Fulbright Student Grant to do research at RWTH Aachen in the 2014-2015 academic year. In Fall 2015 I returned to MIT and received my SM in Aerospace Engineering in 2017. I am a recipient of the National Science Foundation Graduate Research Fellowship and the Fannie and John Hertz Foundation Fellowship.
I am committed to promoting equity in education, and I am proud to have served three years on MIT's Committee on Sexual Misconduct, Prevention, and Response and 4.5 years on the executive board Graduate Women in Aerospace Engineering.
July 2020: Awarded a 2020 SIAM Student Paper Prize for my work on multifidelity estimation of global sensitivity indices (read about it at the SIAM News Blog). I also gave a presentation in the 1st Workshop on Scientific-Driven Deep Learning on July 1 (video available at the link).
June 2020: I gave a LANS Seminar on June 3 at Argonne National Lab.
May 2020: I attended in the Erwin Schrödinger Institute's virtual workshop on "Multilevel and multifidelity sampling methods in UQ for PDEs" May 4-5.
February 2020: Our paper, "Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems," has been accepted for publication the Physica D Special Issue on Machine Learning and Dynamical Systems. This is joint work with Boris Kramer, Benjamin Peherstorfer, and Karen Willcox, and can be downloaded from arXiv here.