Environmental injustice is the inequitable and disproportionate exposure of poor, minority, and disenfranchised populations to toxic chemical and non-chemical stressors in the natural, built, and social environments, over time. Toxic environmental exposures are key components of the social determinants of health and underlying health inequities that are also higher among these populations. Infants and children are especially vulnerable. Childhood is a time of rapid growth and differentiation biologically and is radically different than adult biology and behavior. If the timing of a toxic exposure corresponds to a life stage during which growth is particularly rapid, the potential impact of that exposure is multiplied by offsetting the developmental trajectory of the child. This meeting will bring together academic, government, and community partners to share research findings, discuss the use of computational analytics and artificial intelligence (AI) and machine learning (ML) in analyzing results of large, multi-dimensional data sets, and discuss translational interventions and policies needed to reduce the effects of environmental injustice on child health.