Title: Machine Learning-based Market Design for Adoption Matching
Abstract: In this talk, I will discuss a new market design research project on adoption matching, where the goal is to match children in need of adoptive homes to families. We study a data-driven matching platform that helps adoption agencies find such matches. The goal of our research project is to analyze how this platform can further be improved. I will first give background information on adoption processes in the US and describe how adoption agencies currently use the matching platform. Further, I will talk about some general insights obtained through interviews with employees of an adoption agency that uses this matching platform intensively. Finally, I will sketch possible modeling approaches for adoption matching and present research questions that we are planning to work on in the future.
