This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program grant award of $182,803 to the University of Connecticut (UConn) aims to develop a continual learning paradigm to address challenges in learning on evolving graphs. The project, titled "TOWARDS CONTINUAL LEARNING ON EVOLVING GRAPHS: FROM MEMORIZATION TO GENERALIZATION", seeks to enable intelligent agents to incrementally acquire, perceive, and exploit structural and temporal dynamic knowledge from continuously growing and evolving data. The research will contribute to fields such as graph representation learning, time series analysis, continual learning, and causal analysis, and produce open-source tools for applications like node classification, link prediction, and temporal forecasting. The project will also engage high school students in research, broaden participation of underrepresented groups in STEM, and develop new graduate-level course modules. This award, effective April 1, 2024 through March 31, 2029, reflects NSF's mission to advance scientific knowledge and deliver broader societal impacts.