Fibrosis is a hallmark of numerous diseases, including various cancers, post-infarction cardiac scarring, pulmonary fibrosis, and arteriosclerosis. With minimal available treatment options, fibrosis is implicated in 45% of all deaths in the developed world. Fibrotic diseases are characterized by myofibroblast (MF) differentiation, cellular proliferation and excessive extracellular matrix (ECM) synthesis, subsequently leading to a reorganization of tissue architecture and organ stiffening. Furthermore, while it has been well established that pro-fibrotic cytokines and ECM transformation correlate with MF differentiation and fibrotic progression, how 3D fibrotic ECM specifically affects stromal cell phenotype has been less explored. Despite their lack of canonical MF markers, alternative fibroblastic and endothelial cell subtypes may also be affected by fibrotic ECM and contribute to fibrosis. Thus, the overall focus of this dissertation is to 1) study how a 3D fibrous ECM affects fibroblast phenotype and 2) characterize the diversity of stromal phenotypes present in lung fibrosis. Toward the above, this thesis firstly focuses on the design of a novel 3D fibrous biomaterial model of interstitial ECM and explores how physical attributes of 3D ECM (stiffness, fiber density) regulate the phenotype of primary lung fibroblasts. Using standard hydrogel chemistries and electrospinning methods, a model was established to approximate the fibrillar structure and mechanics of lung interstitial tissue. Our results revealed that crosslinking and stiffness did not directly promote MF differentiation in 3D environments, whereas matrix fiber density was a strong driver of 3D MF differentiation. Furthermore, this differentiation mechanism was dependent upon matrix degradation via MMP activity, Rac1-mediated contact guidance along matrix fibers, and RhoA-mediated cell expansion and contractility. Alternative applications of this model, such as use for a drug screening platform were explored as well. Subsequently, this thesis describes the phenotypic landscape of the human lung in a healthy and fibrotic state. Using clinical transcriptomics data, SC-RNA-SEQ analysis revealed various subtypes within the stromal compartment of the lung, including various fibroblasts, endothelial cells, pericytes, smooth muscle cells, and mesothelial cells. As the primary matrix producing cells, endothelial and fibroblast subtypes were explored in detail, with characterization of key biological pathways and regulators of these distinct cell types. To explore the relevance of the aforementioned fibrous hydrogel model to the native pulmonary microenvironment, transcriptomic analysis was conducted to cross reference with the clinical dataset. Alternative applications of these analyses included the identification of potentially novel regulators and pharmacologic targets which are actively being explored in murine models of fibrosis. Overall, the work presented in this dissertation utilizes tissue engineering and bioinformatics approaches to investigate the fibrotic microenvironment. The data presented here suggests a tight regulation of stromal cell phenotype by 3D matrix fiber density and resultant cell mechanosensing. Furthermore, approaches used in this thesis present a path for the design and application of biomimetic disease models, and, via the combination of transcriptomics data, provide a guidepost for rational model benchmarking and biological discovery.