This $400,000 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research by Arizona State University to advance data-centric artificial intelligence (AI) through generative approaches for feature space reconstruction. The key objectives are to create a more automated and generic framework to distill feature knowledge, convert feature space search into continuous optimization, and enable robust and transferable generative feature transformation. The project aims to incorporate the proposed methods into systems for modeling material formula interactions and reconstructing polymer configuration indicators. The educational component includes developing a new curriculum on data-centric AI and providing research opportunities for underrepresented students. The project will run for three years from September 2024 to August 2027.
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