There are large uncertainties in our future projections of climate change at the regional scale, with spatial variabilities not resolved adequately by coarse-grained Earth System Models (ESMs). In this study, we use pseudo global warming simulations driven by end of the century upper end RCP (Representative Concentration Pathway) 8.5 projections from 11 state-of-the-art ESMs to examine changes in summer heat stress extremes using physiologically relevant heat stress metrics (heat index and wet bulb globe temperature) over the Great Lakes Region (GLR). These simulations, generated from a cloud-resolving model, are at a fine spatiotemporal resolution to detect heterogeneities relevant for human heat exposure. These downscaled climate projections are combined with gridded future population estimates to isolate population versus warming contributions to population-adjusted heat stress in this region. Our results show that a significant portion of summer will be dominated by critical outdoor heat stress levels within GLR for this scenario. Additionally, regions with higher heat stress generally have disproportionately higher population densities. Humidity change generates positive feedback on future heat stress, generally amplifying heat stress (by 24.2% to 79.5%) compared to changing air temperature alone, with the degree of control of humidity depending on the heat stress metric used. The uncertainty of the results for future heat stress are quantified based on multiple ESMs and heat stress metrics used in this study. Overall, our study shows the importance of dynamically resolving heat stress at population-relevant scales to get more accurate estimates of future heat risk in the region.