Emma Hart

  • Program Year: 1
  • Academic Institution: Emory University
  • Field of Study: Computational Mathematics
  • Academic Advisor: Julianne Chung
  • Practicum(s): Practicum Not Yet Completed
  • Degree(s):
    B.A., Applied Mathematics, Colgate University, 2022

Summary of Research

In the first year of my graduate program, I have been interested in inverse problems and uncertainty quantification, especially with applications in medical and atmospheric imaging. Currently, under the mentorship of Julianne and Tia Chung, I am working with autoencoder networks that can supplement traditional inverse problem techniques (in UQ and regularization, for example). More broadly in my research, and throughout my PhD, I hope to learn more methodologies of numerical linear algebra and ways that they can be applied to solve problems in engineering and sustainability.


Emma Hart, Elle Buser, and Ben Huenemann. "Comparison of atlas-based and neural-network-based semantic segmentation for DENSE MRI images." SIAM undergraduate research online, https://doi.org/10.48550/arXiv.2109.14116


Dean's Award for Academic Excellence with Distinction, Colgate University (2018-2022)
Graduate School Access Fund Recipient, Colgate University (2021)
Osborne Mathematics Prize, Colgate University (2021)
Sisson Mathematics Prize, Colgate University (2020)
Charles A. Dana Scholar, Colgate University (2020)
Liberal Arts Core Curriculum Prize, Colgate University (2019)