{"id":925,"date":"2026-01-26T11:57:10","date_gmt":"2026-01-26T16:57:10","guid":{"rendered":"https:\/\/carleton.ca\/camg\/?post_type=cu-people&p=925"},"modified":"2026-01-26T11:58:10","modified_gmt":"2026-01-26T16:58:10","slug":"saeed","status":"publish","type":"cu-people","link":"https:\/\/carleton.ca\/camg\/people\/saeed\/","title":{"rendered":"Saeed"},"content":{"rendered":"
Introduction and Research Interests<\/strong><\/p>\n Saeed Nadi is a Ph.D. candidate in Civil and Environmental Engineering with a research focus on air quality modeling, remote sensing, and geospatial data science. His work integrates satellite observations, chemical transport models, ground-based monitoring data, and advanced machine-learning methods to improve high-resolution estimates of ambient PM2.5 and related air pollutants.<\/p>\n His research emphasizes the development of spatiotemporally explicit prediction frameworks, including ensemble and deep\u00a0learning approaches, uncertainty quantification, and data fusion techniques that combine heterogeneous environmental datasets. Saeed\u2019s work aims to support exposure assessment, health studies, and evidence-based environmental policy by improving the accuracy, interpretability, and robustness of air pollution estimates across continental spatial domains.<\/p>\n","protected":false},"template":"","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_links_to":"","_links_to_target":""},"people-type":[21],"yoast_head":"\n