There are large uncertainties in our future projections of climate change, with regional variabilities not resolved adequately by Earth System Models (ESMs). Here we use pseudo global warming (PGW) simulations using the Weather Research and Forecasting (WRF) model driven by end of the century RCP8.5 projections from 11 ESMs, as well as ensemble projections, to examine changes in summer extreme heat over the Great Lakes Region (GLR). The WRF simulations are at a fine enough spatial resolution (~4 km) to detect heterogeneities relevant for human heat exposure such as the urban versus rural gradient and lake versus land surfaces. Moreover, the temporal resolution (hourly) can better isolate diurnal extremes of temperature and heat stress. These simulations are combined with gridded population projections for the corresponding Shared Socioeconomic Pathway (SSP) to estimate population versus warming contributions to cumulative human exposure to extreme heart in this region. Our results show disproportionately higher increases in overall heat exposure in the GLR than for mean global or land surfaces across model simulations, quantifying population-level heat burden that can inform climate change adaptation strategies.