Wave-particle interactions are a fundamental process underlying phenomena across the plasma universe, from laboratory plasmas to the magnetosphere. Understanding how energetic particles interact with waves in space and laboratory plasmas has the potential to improve our ability to protect satellites, design cleaner energy sources, and develop technologies that rely on controlling high-temperature plasmas. This award supports a collaboration between Columbia University, West Virginia University, and New York University to study how modulations of the background magnetic fields can impact the interactions between energetic particles and plasma waves. Machine learning techniques will be leveraged to discover simplified models that capture the relevant dynamics. In addition to advancing science, this project will support the training of students and early-career researchers, develop interactive classroom tools for K-12 and graduate education, and promote open, accessible science through videos, software, and tutorials. This project will bring together expertise from energetic particle dynamics in magnetic confinement fusion, radiation belt electron transport, and data-driven reduced models to address two fundamental questions: How are resonant wave-particle interactions (WPI) modified by three-dimensional (3D) structure of magnetic fields? and How do 3D magnetic fields modify wave-induced particle transport? These questions will be addressed using two model problems: resonant