I’m a computational behavior scientist modeling complex behavior and physiology systems. I specialize in neuromodulation, longitudinal behavior and physiology tracking, learning mechanisms, estimation statistics, large-dimensional data analysis and visualization, reproducible analysis workflows, and AI agent workflows and evaluation.
I am currently a Senior Research Fellow at the Adam Claridge-Chang Lab. Previously I was a PhD student at the Tonegawa Lab at MIT.
My work asks how we infer hidden states from noisy, high-dimensional evidence. Hunger, satiety, impulsivity, attention, social influence, and model capability are not directly visible. We infer them from behavior, physiology, neural activity, molecular state, and context. Across animals, patients, users, and AI agents, the problem is often the same: infer hidden state from noisy evidence, represent it faithfully, and decide what can be trusted.
Hot Off the Press · Neuroscience · Methods
What Is a Hungry Fly?
Hunger and satiety are not single behaviors — they are coordinated internal states, expressed across many dimensions at once. On tracking thousands of Drosophila to understand how serotonin implements hunger, and what it takes to prove a neural manipulation actually changed the state rather than just one metric.
