Project Summary

This exploratory project mobilizes new computational methods and an interdisciplinary approach to modelling the dynamics of R&D systems and outcomes to pilot a novel, potentially transformative approach that addresses all three fundamental challenges. It merges conceptual models drawn from the sociology and economics of science, evolutionary theory, and organizational theory with large language model semantic embeddings, dynamic graph embeddings, and deep learning models. Integrated metadata for 159 million scientific publications, 170 million international patents, 8 million grants from US and non-US sources and detailed information on more than $10.3 billion of venture investments in nearly 400 technology start-up companies will underpin a new, exploratory analysis to develop and validate models that robustly identify global, multi-sector research for an important C&ET, Quantum Information Science (QIS).