About

I am a student and researcher in theoretical neuroscience and machine learning. I'm interested in how nature finds elegant solutions to complex problems, as well as the pressures or constraints which help to produce them.

Specifically, I study efficiency in natural learning and representations, and focus on models of the cortex. This includes energy-based models (especially predictive coding), network topology, and Cholletian intelligence.

At Mercor, I am a project lead and machine learning researcher.

At Algoverse, I am a machine learning research mentor and senior author.

At Launchpad, I've led and contributed to machine learning research projects, and was the head of education.

At Berkeley, I taught the Linguistics 198 course on linguistic relativity [see syllabus], and am a student in the class of 2026.

This fall, I will be pursuing an MPhil in NeuroAI and Intelligent Systems at Cambridge.

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