I am a programmer and researcher who wants to make computers smarter. This led me from computer science into neuroscience, where I studied the smartest machine that we know of, and then back into AI, since deep learning was going further than I'd ever expected.

I am excited about LLM-based tools, particularly those that could help us discover the next set of AI architectures.

Current projects

Exploring a complexity-forward approach to automating the "outer loop" of machine learning

Building Vexpr, outerloop, and the Outer Loop Cookbook

Recent blog posts

Gaussian Processes Extrapolate, Sometimes in Goofy Ways
2023-03-28

Maybe Bayesian Optimization Should Be Harder, Not Easier
2022-11-30

Imagine A Deep Network That Performs Successive Cheap Queries On Its Input
2022-07-08

Bayesian Optimization Is More Basis-Dependent Than You Might Think
2022-06-26

Likely ≠ Typical: A Viewpoint On Why We Perturb Neural Networks
2022-01-28

Some "Causal Inference" intuition
2021-11-04

Select talks / presentations

Intro to Grid Cells + Quickly Forming Structured Memories
2021-06-07

Testing a possible explanation for grid cell distortions
2021-05-17

Journal Club: Hinton's GLOM + Numenta's TBT (after a year without a haircut)
2021-03-24

Using grid cells as a prediction-enabling basis
2020-12-22

The Minimum Description Length Principle, sparsity, and quantization
2020-04-01

Photo

(Photo credit: Rosanne Liu, 2023)

Papers

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