Hi! I am a researcher at Transluce. I'm interested in understanding language model behaviors and the internal representations behind them, and in building technology to ensure that AI systems act in predictable, interpretable, and beneficial ways.

I'm especially interested in understanding how distinctive "personas" emerge in language models, and studying the relationship is between the model weights, the narrative structure of the model's inputs and outputs, and the behavioral tendencies and broader "character archetypes" in the model at inference time. I'm also very interested in how we can build better tools as a community for understanding and predicting model behaviors.

During my PhD at the University of Toronto, I studied how to get powerful models to accurately report their uncertainty, so that we know when to trust them even if we can't directly verify their reasoning. You can read more about this in my blog post on "uncertain simulators" and my paper "Experts Don't Cheat". I've also explored ways to summarize the uncertainty in generative models of code, described in my paper about the R-U-SURE system.

While at Google DeepMind, I released a JAX neural network library, Penzai, and an interactive pretty-printer, Treescope, that together make it easy to inspect, modify, and visualize parts of pretrained models. I designed Penzai and Treescope with the hope that they could lower the barrier of entry for research into understanding neural networks and steering them toward safe behaviors.

In the past, I have worked on generative models of discrete data structures (such as trees, sets, and graphs), theoretical analyses of self-supervised learning, a strongly-typed language (Dex) for building unconventional machine learning models, generative models for music, and many others. See my research page for more information.

I worked at Google Brain and Google DeepMind from 2019 to 2024, first as an AI Resident and later as a Research Scientist. Before that, I worked on applied machine learning at Cruise from 2018 to 2019. I received my Bachelor's degree from Harvey Mudd College in 2018 as a CS/Math joint major, where I did research on applying deep learning to music generation and worked as a math tutor in the Academic Excellence tutoring program.

In my free time, I enjoy playing board games and indie video games (current recommendations: Outer Wilds, Baba is You, A Monster's Expedition, Balatro, Tunic), reading about math and programming languages, and telling myself that someday I'll get back into making music.