The human brain comprises a remarkable variety of cell types that collectively support sensation, cognition, and behavior. This diversity arises not from differences in genetic code, but from how DNA is physically organized and regulated in each cell. Understanding the 3D structure of the genome – and how it controls which genes are active in different brain cells – is essential for advancing neuroscience, regenerative medicine, and genome engineering. This project will use AI to investigate how chromatin accessibility, spatial DNA structure, and gene activity work together to establish cell identity in the human brain. The team will build new AI tools to reconstruct the three-dimensional organization of chromosomes from single-cell experiments and to simulate how changes in genome structure affect gene expression. These efforts will create a detailed map of chromatin structure across brain cell types and provide computational models to explain how genetic information is interpreted differently in different cells. The results will support basic research on brain development and disease, and will help guide future interventions based on genome editing. The project will also generate community resources such as open-source software and public data releases, and will provide training opportunities for early-career researchers. This research brings together computational biophysics, machine learning, and genomics to develop a unified generative framework for modeling chromatin