Nate Gruver

I am a machine learning PhD student at NYU Courant advised by Andrew Gordon Wilson and working closely with Kyunghyun Cho.

I received a BS/MS in computer science from Stanford University, where I worked with Stefano Ermon, Mykel Kochenderfer, and Chris Piech.

I spent my last two summers working on generative modeling for applications in chemistry and biology at FAIR. I've also spent time at Waymo, Apple, and Google.

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I work on deep learning with two primary focuses:

1. Generative models for biology and chemistry [1, 2]
2. Understanding the role of inductive biases and the extent to which hand-crafted architectures can be replaced with large-scale pretraining [1, 2]