Conference Papers

  • M. Trautner, G. Margolis, and S. Ravela, "Informative Neural Ensemble Kalman Learning." DDDAS-2020. (arxiv)


  • B. Liu, M. Trautner, A. M. Stuart, K. Bhattacharya. "Learning Macroscopic Internal Variables and History Dependence from Microscopic Models," 2022. (arxiv).

  • *K. Bhattacharya, B. Liu, A. Stuart, and M. Trautner. "Learning Homogenized Markovian Models in Viscoelasticity," 2022. (arxiv)

  • M. Trautner, Z. Li, and S. Ravela, "Learn Like The Pro: Norms from Theory to Size Neural Computation," 2021. (arxiv)

*denotes alphabetical order


  • Thomas A. Tisch Prize for Graduate Teaching in Mathematics (Caltech, 2022)

  • Rhodes Scholarship Finalist (2020)

  • NCAA Elite 90 Award for highest GPA and credit-hours among national track championship qualifiers (2019)

  • MathWorks Math Modeling Challenge National Champion (2016)