It is well understood that genetic information encoded in DNA is passed on to future generations. However, genetic information can be modified without altering the DNA sequence, and these modifications can be passed on to future generations. Epigenetics is the study of this processes which shapes the three-dimensional organization of DNA and thus controls gene activity. Dysregulation of epigenetic processes has been implicated in numerous human diseases. Despite decades of research, the precise "epigenetic grammar" -- the rules by which specific combinations of epigenetic modifications collectively shape chromatin structure -- remains elusive. Understanding these molecular mechanisms is critical for advancing fundamental biology and improving the diagnosis and treatment of human diseases. This project will integrate artificial intelligence (AI) with physics-based computational simulations to uncover how epigenetic regulation modulates chromatin structure and function, including its role in the dynamic compartmentalization of DNA within the cell. This project aims to establish detailed molecular links between specific epigenetic modifications and genome function, guiding the rational design of therapeutic strategies targeting epigenetic dysregulation. The tools and methods developed through this project will enable predictive, mechanistic studies of biomolecular assemblies beyond chromatin. The educational activities will launch an AI-visualization suite to engage students from K-12 to graduate levels, both regionally and nationally, in data science, computational modeling, and biomolecular visualization. This project employs a predictive, sequence- and epigenetic-specific simulation model to investigate how epigenetic modifications and regulatory proteins modulate chromatin organization. A central computational challenge in studying epigenetic regulation is the need to simultaneously model large-scale chromatin organization and fine-grained chemical interactions