The challenge of systematically modifying and optimizing regulatory elements for precise gene expressioncontrol is central to modern genomics and synthetic biology. Advancements in generative AI have paved theway for designing synthetic sequences with the aim of safely and accurately modulating gene expression. We leverage diffusion models to design context-specific DNA regulatory sequences, which hold significantpotential toward enabling novel therapeutic applications requiring precise modulation of gene expression. Our framework uses a cell type-specific diffusion model to generate synthetic 200 bp regulatory elements based on chromatin accessibility across different cell types. We evaluate the generated sequences based on key metricsto ensure they retain properties of endogenous sequences: transcription factor binding site composition,potential for cell type-specific chromatin accessibility, and capacity for sequences generated by DNA diffusionto activate gene expression in different cell contexts using state-of-the-art prediction models. Our resultsdemonstrate the ability to robustly generate DNA sequences with cell type-specific regulatory potential. DNA-Diffusion paves the way for revolutionizing a regulatory modulation approach to mammalian synthetic biologyand precision gene therapy.