The Lab for Symbolic and Data-Driven AI explores how symbolic reasoning and data-centric methods can be integrated to advance both the foundations and frontiers of artificial intelligence. By placing equal emphasis on formal methods and contemporary AI—such as large-scale models and neural architectures—we aim to shape the evolving AI landscape through a synthesis of theoretical rigor and empirical insight. Our research investigates how uniting these two paradigms can lead to AI systems that are not only more interpretable, robust, and adaptable, but also trustworthy and ethically grounded. Through interdisciplinary collaboration, we strive to bridge symbolic AI with the rapidly advancing capabilities of modern machine learning.