Kamarin Lee

I build data and AI systems. My independent research asks a simple question: what should an investor know about a financial number before using it to make a decision?

I study where a number came from, which definitions shaped it, and who made the judgments behind it. The goal is to help investors tell the difference between a review that happened and a result they can rely on.

My work grows out of more than a decade in data and AI. I focus on decisions investors already make: comparing opportunities, pricing uncertainty, and deciding where capital should go.

I am interested in when a safeguard becomes useful evidence. Good evidence does not remove judgment. It shows what a decision depends on, what remains uncertain, and what could change the answer.