Margaret Trautner

  • Program Year: 4
  • Academic Institution: California Institute of Technology
  • Field of Study: Computing and Mathematical Sciences
  • Academic Advisor: Andrew Stuart
  • Practicum(s):
    Sandia National Laboratories, New Mexico (2021)
  • Degree(s):
    B.S. Mathematics, Massachusetts Institute of Technology, 2020
  • Personal URL:


Bhattacharya, K., Kovachki, N., Rajan, A., Stuart, A. M., & Trautner, M. (2023). Learning Homogenization for Elliptic Operators. arXiv preprint arXiv:2306.12006.
Liu, B., Ocegueda, E., Trautner, M., Stuart, A. M., & Bhattacharya, K. (2023). Learning macroscopic internal variables and history dependence from microscopic models. Journal of the Mechanics and Physics of Solids, 105329.
Learning Markovian homogenized models in viscoelasticity
K Bhattacharya, B Liu, A Stuart, M Trautner - Multiscale Modeling & Simulation, 2023
Trautner M., Margolis G., Ravela S. (2020) Informative Ensemble Kalman Learning for Neural Structure. In: Darema F., Blasch E., Ravela S., Aved A. (eds) Dynamic Data Driven Application Systems. DDDAS 2020. Lecture Notes in Computer Science, vol 12312. Springer, Cham.
Trautner, M., and Ravela, S., Neural Integration of Continuous Dynamics, (2019), preprint,


Thomas A. Tisch Prize for Graduate Teaching in Mathematics at Caltech, 2022.
Rhodes Scholarship Finalist, District XIII, 2019.
NCAA Elite 90 Award (highest GPA at national competition site), 2019.
CoSIDA Academic All-American 2019
National Merit Scholar, 2016.
Moody's Corporation Math Challenge Champion, 2016.