• 2025 (expected)
    PhD in Applied Mathematics
    Yale University
    • Advised by Ronald Coifman and Yuval Kluger.
  • 2017
    B.S. in Computer Science and Mathematics
    Yale University


  • 2023
    Machine Learning Research Intern
    Bosch Center for Artificial Intelligence
    • Researching (1) robust training-free approaches to guided diffusion models using optimal control and (2) image-to-image translation using algebraically reversible solvers for the Schrodinger Bridge problem. Submitted to ICML 2024.
  • 2020
    Machine Learning Research Intern
    Center for Computational Mathematics, Flatiron Institute
    • Explored deep image prior-based techniques for enhancing phase retrieval in low-photon settings at the Center for Computational Mathematics (CCM) at Flatiron Institute
  • 2016
    Software Engineering Intern
    Amazon Lab126
    • Modified machine learning module (an n-gram Markov model) in FireOS to reduce memory usage by ~2x with no significant reduction in prediction quality