Better to marry renewables than to burn fossil fuels in border states
Aimee Maurais, Arianna Krinos, "Better to marry renewables than to burn fossil fuels in border states." The Journal of Undergraduate Mathematics and its Applications, 2018.
CV
Education
- S.M. Computational Science and Engineering, Massachusetts Institute of Technology, 2022
- B.S. Mathematics, Virginia Tech, 2019
- B.S. Computational Modeling and Data Analytics, Virginia Tech, 2019
Work Experience
- MIT Lincoln Laboratory: Associate Technical Staff (2019-2021)
- Modeling and simulation, algorithm design, and software development for threat detection
Selected Honors
- National Science Foundation Graduate Research Felllow, 2020-2025
- College of Science Outstanding Senior, Virginia Tech, 2019
- Mathematical Contest in Modeling Outstanding Winner, 2018 & 2019
Publications
Computational Tools for Bayesian Inverse Problems with Python Implementations
Aimee Maurais, "Computational Tools for Bayesian Inverse Problems with Python Implementations." Undergraduate Honors Thesis, 2019.
Nuggets of Wisdom from Destinations Doomed Due to Dragon Dominion
Aimee Maurais, Arianna Krinos, "Nuggets of Wisdom from Destinations Doomed Due to Dragon Dominion." The Journal of Undergraduate Mathematics and its Applications, 2019.
Parameter and Uncertainty Estimation for a Model of Atmospheric CO$_2$ Observations
Aimee Maurais, Arianna Krinos, "Parameter and Uncertainty Estimation for a Model of Atmospheric CO$_2$ Observations." SIAM Undergraduate Research Online, 2019.
Multifidelity Covariance Estimation Three Ways
Aimee Maurais, "Multifidelity Covariance Estimation Three Ways." Master's Thesis, 2022.
Multi-fidelity covariance estimation in the log-Euclidean geometry
Aimee Maurais, Terrence Alsup, Benjamin Peherstorfer, Youssef Marzouk, "Multi-fidelity covariance estimation in the log-Euclidean geometry." In International Conference on Machine Learning. PMLR, 2023.
Multifidelity covariance estimation via regression on the manifold of symmetric positive definite matrices
Aimee Maurais, Terrence Alsup, Benjamin Peherstorfer, Youssef Marzouk, "Multifidelity covariance estimation via regression on the manifold of symmetric positive definite matrices." arXiv:2307.12438, 2023.
Adaptive algorithms for continuous-time transport: homotopy-driven sampling and a new interacting particle system
Aimee Maurais and Youssef Marzouk, "Adaptive algorithms for continuous-time transport: homotopy-driven sampling and a new interacting particle system." NeurIPS Workshop on Optimal Transport and Machine Learning, 2023.
Sampling in Unit Time with Kernel Fisher-Rao Flow
Aimee Maurais and Youssef Marzouk, "Sampling in unit time with kernel Fisher-Rao flow." arXiv:2401.03892, 2024.
Talks
Parameter and Uncertainty Estimation for a Model of Atmospheric CO2 Observations
Talk at Virginia Tech Department of Mathematics, Blacksburg, VA
Better to Marry Renewables than Burn Fossil Fuels with Passion
Conference Presentation at MAA Mathfest, Denver, CO
Multifidelity Covariance Estimation Three Ways
Conference Presentation at SIAM Conference on Uncertainty Quantification, Atlanta, GA
Riemannian Multifidelity Covariance Estimation from Statistically Coupled Observations
Talk at Dartmouth College Department of Mathematics, Hanover, NH
Riemannian Multifidelity Covariance Estimation from Statistically Coupled Observations
Conference Presentation at SIAM Conference on Computational Science and Engineering, Amsterdam, NL
Riemannian Multifidelity Covariance Estimation from Statistically Coupled Observations
Talk at MIT Aerospace Computational Science and Engineering Lab Seminar, Cambridge, MA
Sampling in Unit Time with Kernel Fisher-Rao Flow
Conference Presentation at SIAM Conference on Uncertainty Quantification, Trieste, Italy
Teaching
Service and Outreach
- Broader Engagement (BE) Committee, Sustainable Horizons Institue, 2019-Present
- Housing Chair, BE at SIAM Mathematics of Data Science 2022
- Social Chair and Gather.town Czar, BE at SIAM Computational Science and Engineering 2021
- Recent College Graduate Employee Resource Group Committee, MITLL, 2020-2021
- Women in Data Science Blacksburg Co-Ambassador, 2019