Measuring and improving the innovative potential of research and translation through temporal knowledge graph embedding
Project Summary
This project will benefit public health by developing advanced computational methods to model the evolution of scientific knowledge and predict how individual researchers and interdisciplinary teams contribute to groundbreaking discoveries in biomedical research at todays frontiers and over decades. By modeling team dynamics, identifying emerging areas of innovation, and predicting long-term research trajectories, this use-inspired project will enhance funder and investigator capabilities to identify and successfully pursue novel, high-risk, high-return projects in biomedical and other STEM fields while contributing to fundamental knowledge in several related social and computational science areas. Improved models and tools can inform problem selection and team assembly strategies, potentially leading to breakthroughs in intractable but critical areas such as mental health, addiction, and aging-related diseases, ultimately improving public health outcomes.