My Ph.D. is in Geography and Social Data Analytics specializing in fusing sources of geographic information to better understand complex environments. I joined the Geoinformatics and Earth Observation Laboratory (GEOlab) in 2014 to pursue research using computational methods for spatio-temporal analysis and modeling of environmental hazards in relation to human impacts during disasters. My research has involved the use of machine learning to predict spatial behaviors, the application of geospatial technologies during hazards, and the utilization of crowdsourced environmental monitoring data. My master’s thesis was on the validation of citizen science radiation measurements around Fukushima by developing a methodology to compare the Volunteered Geographic Information (VGI) to government data and dispersion models over space and time. My Ph.D. research continued on this theme by assessing the validity, resolution, and usefulness of citizen-contributed environmental hazard data. My postdoctoral research involves Artificial Intelligence (AI) approaches to assess emissions using hyperspectral imagery. I believe it is critical to recognize the benefits and limitations of environmental and social data from various geospatially enabled technologies.