Nathan is a robot learning researcher, writer, non-professional athlete, and a mental-health advocate.

There really is too much noise.

I do my best to only contribute high signal content on machine learning, human optimization, and the nature of life.

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ML/RL & Microrobotics

A memo I wrote to my research group on the open questions when applying machine learning to another research area: novel microrobotics.


Lifelong Learning 2021

What I have been learning from recently.


Robot learning, model-based RL, and related optimization at NeurIPs 2020

What I learned about deep RL and model-based learning at NeurIPs 2020.

More musings →


Axes for Sociotechnical Inquiry in AI Research

We present a concise set of directions for understanding the societal risks of new directions of AI research.

MBRL-Lib: A Modular Library for Model-based Reinforcement Learning

An open-source PyTorch repository designed from the bottom up for model-based reinforcement learning research.
More papers →