11-15, 10:20–10:30 (Asia/Bangkok), Stage 5
I aim to achieve effective public goods funding by comparing grants models. Grants programs are key in the crypto ecosystem, but comparative studies are rare. Our study compares Uniswap, dYdX, Optimism, Gitcoin, and more, categorizing them into "top-down," "bottom-up," and "QF (algorithmic)" types. Findings suggest bottom-up and QF types distribute funds more evenly with smaller variability and grant amounts, while top-down types show greater variability with larger grants for fewer grantees.
He is a part of Fracton Research, and contributes to the public goods space. He is an ex-reviewer of Polygon Community Grants Program, a contributor of Dig DAO, and a contributor of Grant Innovation Lab by MetaGov. Especially, he analyzes grants programs and grants DAOs by quantitatively cross-comparing them to achieve better, more effective, and fairer programs. He finally aims to evaluate and measure impacts and outcomes in public goods funding.