About me

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

Research interests

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

My projects have included:

• Depth separation of neural networks in terms of learning capabilities
• Representation costs of deep neural networks
• Detecting branching structure in data
• Eigenvalue methods for multivariate numerical rootfinding