{"id":12581,"date":"2025-01-17T08:33:21","date_gmt":"2025-01-17T06:33:21","guid":{"rendered":"https:\/\/geosense.ro\/?post_type=team&#038;p=12581"},"modified":"2026-03-24T12:22:26","modified_gmt":"2026-03-24T10:22:26","slug":"teodor-costachioiu","status":"publish","type":"team","link":"https:\/\/geosense.ro\/ro\/team\/teodor-costachioiu\/","title":{"rendered":"Teodor COST\u0102CHIOIU"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"12581\" class=\"elementor elementor-12581\">\n\t\t\t\t<div class=\"elementor-element elementor-element-29de4426 e-flex e-con-boxed e-con e-parent\" data-id=\"29de4426\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-4f4c801c elementor-widget elementor-widget-text-editor\" data-id=\"4f4c801c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<p data-start=\"228\" data-end=\"719\"><strong data-start=\"228\" data-end=\"250\">Teodor Cost\u0103chioiu<\/strong> is a Research Scientist at the <strong data-start=\"291\" data-end=\"314\">GeoSense Laboratory<\/strong>, Politehnica University of Bucharest. He joined GeoSense in <strong data-start=\"375\" data-end=\"392\">December 2024<\/strong>, where he contributes to the <strong data-start=\"422\" data-end=\"433\">AI4RISK<\/strong> project, developing AI-based methods for multi-source data fusion and predictive risk assessment.<\/p>\n<p data-start=\"228\" data-end=\"719\">His current work integrates Earth-observation data with advanced machine learning and retrieval-augmented generation (RAG) systems to support environmental monitoring and risk analysis.<\/p>\n<p data-start=\"721\" data-end=\"1258\">He received his <strong data-start=\"737\" data-end=\"797\">degree in Electronics and Telecommunications Engineering<\/strong> (a five-year program equivalent to M.Eng.) from Politehnica University of Bucharest in <strong data-start=\"888\" data-end=\"896\">1997<\/strong>, and his <strong data-start=\"906\" data-end=\"941\">Ph.D. in Electronic Engineering<\/strong> from the same university in <strong data-start=\"970\" data-end=\"978\">2011<\/strong>. His doctoral research introduced a novel approach for spatio-temporal change detection using the <strong data-start=\"1077\" data-end=\"1114\">Latent Dirichlet Allocation (LDA)<\/strong> algorithm, originally developed for text analysis, to model land-cover dynamics in satellite image time series of the Bucharest\u2013Ilfov region.<\/p>\n<p data-start=\"1260\" data-end=\"1780\">Between <strong data-start=\"1268\" data-end=\"1285\">2011 and 2014<\/strong>, he was a Research Scientist at the CEOSpaceTech Research Center, where he contributed to the LEOSITS (Long-Term Data Exploitation for Satellite Image Time Series) project. His work during this period focused on the development of algorithms for spatiotemporal information extraction from large satellite archives.<\/p>\n<p data-start=\"1782\" data-end=\"2030\">His research interests include <strong data-start=\"1813\" data-end=\"1846\">remote-sensing data analytics<\/strong>, <strong data-start=\"1848\" data-end=\"1878\">AI-driven change detection<\/strong>, <strong data-start=\"1880\" data-end=\"1912\">explainable machine learning<\/strong>, and the application of <strong data-start=\"1937\" data-end=\"1962\">large language models<\/strong> for semantic interpretation of multimodal Earth-observation data.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Teodor Cost\u0103chioiu is a Research Scientist at the GeoSense Laboratory, Politehnica University of Bucharest. He joined GeoSense in December 2024, where he contributes to the AI4RISK project, developing AI-based methods for multi-source data fusion and predictive risk assessment. His current work integrates Earth-observation data with advanced machine learning and retrieval-augmented generation (RAG) systems to support [&hellip;]<\/p>\n","protected":false},"featured_media":12491,"parent":0,"menu_order":4,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false},"class_list":["post-12581","team","type-team","status-publish","has-post-thumbnail","hentry"],"acf":{"social_one":"bi bi-google","social_one_link":"https:\/\/scholar.google.com\/citations?user=zC9VzB0AAAAJ&hl=en","social_two":"bi bi-linkedin","social_two_link":"https:\/\/www.linkedin.com\/in\/tcostachioiu\/","social_three":"bi bi-github","social_three_link":"https:\/\/github.com\/tcostachioiu\/","social_four":"","social_four_link":""},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/team\/12581","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/team"}],"about":[{"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/types\/team"}],"replies":[{"embeddable":true,"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/comments?post=12581"}],"version-history":[{"count":25,"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/team\/12581\/revisions"}],"predecessor-version":[{"id":13428,"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/team\/12581\/revisions\/13428"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/media\/12491"}],"wp:attachment":[{"href":"https:\/\/geosense.ro\/ro\/wp-json\/wp\/v2\/media?parent=12581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}