Cognition
What cortex does with quantity, meaning and song, measured from natural stimuli.
Number, space and time · Birdsong in state space
Co-founder, Erised AI PhD, UC Berkeley
Computational neuroscientist. At Erised, building AI-native instruments for the nanoscale, and the world model their measurements will train.
For about ten years I’ve been asking a version of the same question, first in philosophy and then in physics: how does meaning come out of mechanism, and how would you know if it had?
The answer I’ve settled into is that structure lives in the data, and intelligence is whatever extracts it. That puts the constraint in a slightly unfashionable place. How clever the model is matters less than whether the measurement got made at all, and whether it got made somewhere rich enough that the structure survived contact with the experiment.
Most of what I’ve worked on has been messy on purpose for that reason. Stories instead of word lists. Actual birdsong. Patients at home rather than in a clinic room.
Now
Erised AI builds AI-native systems and world models for nanoscience and metrology: instruments that get smarter with every measurement, because the measurement and the model are designed together. I co-founded it, and I lead the AI, data and computational microscopy side.
The argument that led here is the one in my thesis introduction. In neuroscience, and just as much in materials and devices, the bottleneck is not the supply of hypotheses but the supply of dense, well-designed measurement in the regimes where a system actually operates. That constraint lives in the instrument, so the instrument is what I am building. The note says why.
Research
Closed loop
Recording and stimulation in one circuit, measured in people’s homes rather than a clinic.
Parkinson’s, measured at home
Bayesian
What a fitted weight is entitled to mean, and what the features have to look like before it means anything.
Semantic-cortical atoms, NeurIPS 2026 oral · Sparse concept atoms, NeurIPS 2025
to now
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I wrote my undergraduate philosophy thesis on AlphaGo, mostly while the matches against Lee Sedol were happening.
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Then two years at Penn on birdsong with Vijay Balasubramanian and Eve Armstrong, reconstructing state spaces from recordings to see whether the dynamics carried anything people were throwing away by treating song as acoustics.
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At Berkeley I built encoding models that predict cortical responses from language model features, using two hours of people listening to stories told on The Moth Radio Hour rather than controlled stimuli.
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Now
Now I build characterization instruments.
Contact
If you are building, buying or backing nanoscale measurement, or want to work on the models behind it, I would like to hear from you.
Otherwise: camping, mountains, ballet, and I still read philosophy.