{"id":43547,"date":"2026-10-11T07:19:05","date_gmt":"2026-10-11T07:19:05","guid":{"rendered":"https:\/\/uomosul.edu.iq\/en\/computerscience\/?p=43547"},"modified":"2026-10-11T07:19:05","modified_gmt":"2026-10-11T07:19:05","slug":"1-771","status":"publish","type":"post","link":"https:\/\/uomosul.edu.iq\/en\/computerscience\/2026\/10\/11\/1-771\/","title":{"rendered":"Scientific Workshop Titled: Spatial Statistics Integrated with Artificial Intelligence for Assessing Climate Change Risks"},"content":{"rendered":"<p>Under the patronage and supervision of the Dean of the College of Computer Science and Mathematics, Prof. Dr. Duha Bashir Abdullah, the Department of Statistics and Informatics at the College of Computer Science and Mathematics held a scientific workshop titled: &#8220;Spatial Statistics Integrated with Artificial Intelligence for Climate Change Risk Assessment.&#8221;<\/p>\n<p>**Lecturer**<\/p>\n<p>Asst. Prof. Dr. Manaf Hazim Ahmed<\/p>\n<p>Associate Dean for Scientific Affairs<\/p>\n<p>**Objective**<\/p>\n<p>Iraq is ranked as the fifth most vulnerable country globally to water and food shortages and extreme temperatures. This situation necessitates an analysis of these phenomena and an understanding of their spatial distribution to support decision-making.<\/p>\n<p>The workshop aims to present a methodological approach for integrating spatial statistics and artificial intelligence into climate change risk assessment. This involves modeling the spatial dependency structures of extreme phenomena and estimating the probabilities of their simultaneous occurrence, intensity, and geographic extent. The workshop focuses on combining statistical inference with deep learning models to extract complex relationships from data\u2014while validating models and estimating uncertainty\u2014to identify the most affected areas, support decision-making, and prioritize climate change adaptation strategies.<\/p>\n<p>**Abstract**<\/p>\n<p>The workshop addresses the integration of spatial statistics and deep learning in the analysis of extreme climate phenomena, with a specific focus on temperatures in Iraq. It highlights the importance of spatial dependency in estimating the simultaneous occurrence, intensity, and geographic extent of these events. Furthermore, it covers model validation, uncertainty estimation, and the generation of maps to support risk assessment and climate change adaptation efforts. Target Audience<\/p>\n<p>Faculty members and researchers in statistics, mathematics, computer science, and artificial intelligence.<br \/>\nGraduate students specializing in statistics, data science, computer science, artificial intelligence, and related fields.<br \/>\nResearchers and specialists in climate science, environmental science, and meteorology.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Under the patronage and supervision of the Dean of the College of Computer Science and Mathematics, Prof. Dr. Duha Bashir Abdullah, the Department of Statistics and Informatics at the College of Computer Science and Mathematics held a scientific workshop titled: &#8220;Spatial Statistics Integrated with Artificial Intelligence for Climate Change Risk Assessment.&#8221; **Lecturer** Asst. Prof. Dr. Manaf Hazim Ahmed Associate Dean for Scientific Affairs **Objective** Iraq is ranked as the fifth most vulnerable country globally to water and food shortages and extreme temperatures. This situation necessitates an analysis of these phenomena and an understanding of their spatial distribution to support decision-making. The <a href=\"https:\/\/uomosul.edu.iq\/en\/computerscience\/2026\/10\/11\/1-771\/\"> [Read More]<\/a><\/p>\n","protected":false},"author":24,"featured_media":43548,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[],"class_list":["post-43547","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-workshops"],"_links":{"self":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/43547","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/users\/24"}],"replies":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/comments?post=43547"}],"version-history":[{"count":1,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/43547\/revisions"}],"predecessor-version":[{"id":43549,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/posts\/43547\/revisions\/43549"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/media\/43548"}],"wp:attachment":[{"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/media?parent=43547"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/categories?post=43547"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/uomosul.edu.iq\/en\/computerscience\/wp-json\/wp\/v2\/tags?post=43547"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}