About me

I am a PhD candidate in the Committee on Computational and Applied Mathematics at the University of Chicago graduating in June 2026.

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Research interests

Deep learning, neural networks, optimization, and more generally analysis of algorithms for data science.

My projects have included:

• Analyzing how neural networks adapt to structure in data when trained with gradient descent
• Depth separation of neural networks in terms of learning capabilities
• Representation costs of deep neural networks
• Effect of linear layers in neural networks
• Eigenvalue methods for multivariate numerical rootfinding