Applied Mathematician
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I am an applied mathematician, specializing in mathematical modeling, numerical methods and scientific computing. I have experience working under pressure, breaking down complex problems for non-technical audiences, and consistently delivering high-quality results on any task assigned to me.
My team developed a 2D fluid dynamics model using numerical and dimension reduction methods to simulate tear film thickness, pressure, and osmolarity, aiming to improve the understanding of dry eye disease. Our primary objective was to estimate osmolarity from fluorescent images. To enhance predictive accuracy, we trained neural networks for operator learning, incorporating Fourier Neural Operators (FNO), Fourier Feature Networks (FFN), and DeepONets on 1D and 2D tear film simulations.
The training dataset consisted of 51 × 601 × 30,000 spatial-temporal points, achieving an average relative testing error of 1%.
University of Delaware, PhD in Applied Mathematics (GPA = 3.7) July 2025
Union College, BS in Mathematics and Francophone Studies (GPA = 3.65) June 2020
