Alex Ho | I’m a Ph.D. candidate in Applied Mathematics at UC Merced, where I work at the intersection of inverse problems and numerical optimization. My research focuses on using PDE-constrained optimization to estimate physical parameters — such as diffusion coefficients — in complex environmental systems like marine lakes. I develop efficient algorithms that combine traditional numerical methods with modern machine learning techniques to tackle ill-posed problems, improve interpretability, and support real-world decision-making.

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