E. Qian, B. Kramer, B. Peherstorfer, and K. Willcox, "Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems." Physica D: Nonlinear Phenomena, 2020 (Special Issue on Machine Learning and Dynamical Systems). [Download]
E. Qian, B. Peherstorfer, D. O’Malley, V. Vesselinov, K. Willcox, “Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices.” SIAM Journal on Uncertainty Quantification 2018 6:2, 683-706. [Download] [GitHub]
E. Qian, M. Grepl, K. Veroy, K. Willcox, “A Certified Trust Region Reduced Basis Approach to PDE-Constrained Optimization.” SIAM Journal on Scientific Computing 2017 39:5 S434-S460. [Download]
Q. Wang, S. Gomez, P. J. Blonigan, A. L. Gregory, E. Qian, “Towards Scalable Parallel-in-time Turbulent Flow Simulations.” Physics of Fluids 2013 25:11. [Download]
E. Qian, "A Scientific Machine Learning Approach to Learning Reduced Models for Nonlinear Partial Differential Equations." PhD Thesis, Massachusetts Institute of Technology, 2020.
E. Qian, “A Certified Reduced Basis Approach to PDE-Constrained Optimization.” SM Thesis, Massachusetts Institute of Technology, 2017.
E. Clements [et al., including E. Qian], “TERSat: Trapped Energetic Radiation Satellite.” Proceedings of the 2012 AIAA/USU Conference on Small Satellites, Growing the Community, SSC12-VII-3. [Download]
K. Swieringa, C. Hanson, J. Richardson, J. White, Z. Hasan, E. Qian, A. Girard, “Autonomous Battery Swapping System for Small-scale Helicopters.” In Robotics and Automation (ICRA), 2010 IEEE International Conference, pp. 3335-3340, 3-7 May 2010. [Download from IEEE Xplore]