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 I think about AI agent workflows and evaluation. 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.
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.
Read This Now · Neuroscience · Methods
When one metric lies, the whole behavioral profile tells the truth.
A hungry fly does not only eat more. It searches differently, climbs differently, loiters near food differently, takes bigger meals, and changes how it moves after eating. Hunger and satiety are coordinated internal states, expressed across many behavioral dimensions at once.
Visualization · Uncertainty
An uncertainty-aware heatmap cell that keeps the distribution visible.
AI Workflows · Evaluation
Designing an inspectable loop for scientific judgment, critique, and repair.
Quantified Self · Measurement
Health is multidimensional; recovery is not a single number.
