About

I'm interested in how nature finds elegant solutions to complex problems, often under intense resource constraints which enforce robustness.

My work aims to understand both these solutions and the processes which create them, especially with regard to intelligence.

Specifically, I study theoretical neuroscience and machine learning, working on models of cortical computation with predictive coding.

Outside of this program, I conduct research in general machine learning (mechinterp, world models, other fields), and mentor projects at Algoverse. See publications for more details.

My other academic passions include linguistics and economics. The former appears in much of my past and current work, as it provides a nice microchosm of broader intelligence, and is itself a remarkably powerful faculty thereof.

I was a student in the class of 2026 at Berkeley, and will be at Cambridge in the fall for an MPhil in NeuroAI and Intelligent Systems (2026-2027).

I am happy to talk about research, collaboration, or breaking into the field; feel free to contact me.