This project addresses the topic of global social innovation in science capacity in the face of the COVID-19 pandemic. The pandemic massively disrupted science worldwide, and the purpose of this project is to understand how teams have innovated to minimize these effects on their research activities. We focus on three intertwining features of the social dynamics of international collaborative teams: Social innovation, Adaptation and Resilience, and Learning and Transferability. Social innovation refers to new and different ways of modifying individual and group behavior within the context of team science. The project involves a series of case studies focused around distinct internationally collaborative teams funded through the US NSF or the European Commission. We focus on teams that are new emergent collaborations that establish norms for interaction during the pandemic but also adaptive collaborations that adjust to the barriers and constraints of the pandemic. We use a novel methodological approach to identifying teams using advanced computing techniques in a new and robust bibliometric dataset, complemented by other snowball sampling techniques. The project will conclude with an international workshop to share and disseminate findings that further international collaboration.