Dr. Pedram Fard is a data scientist with the Clinical Augmented Intelligence (CLAI) group, where his research applies computational methods and artificial intelligence (AI) to address limitations of conventional environmental modeling. His current work is centered on developing the national database of air pollution exposure and contributing to large-scale data curation for supporting medically specialized LLMs. Pedram has conducted research on developing methods for entropy-based spatial clustering, which have broad implications in environmental exposure assessment and population-based epidemiology. His creation of Dynamic Activity Cluster Zones (DACZ) and Urban Activity Clusters (UAC) provides more effective alternatives to traditional analysis zones like census blocks and zip codes, which have been widely criticized for their analytical limitations. Dr. Fard earned his PhD in Planning from the University of Waterloo in Canada, specializing in built environment and transportation system modeling. Following his doctoral studies, he completed postdoctoral research and training in Dr. Chirag Patel’s exposome lab at Harvard Medical School, where he contributed to high-profile environmental exposure assessment studies. His work there included participation in an NIH-funded project (2022-2025) examining the health impacts of extreme heat and cold events on aging populations with Alzheimer’s disease and related dementia (ADRD).