{"id":6775,"date":"2022-04-18T15:39:25","date_gmt":"2022-04-18T13:39:25","guid":{"rendered":"https:\/\/www.esme.fr\/recherche\/?post_type=team&#038;p=6775"},"modified":"2026-03-24T11:45:24","modified_gmt":"2026-03-24T10:45:24","slug":"amylia-ait-saadi","status":"publish","type":"team","link":"https:\/\/www.esme.fr\/recherche\/chercheur\/amylia-ait-saadi\/","title":{"rendered":"Amylia Ait Saadi"},"content":{"rendered":"\n<p><strong>Overview of research area<\/strong><\/p>\n\n\n\n<p>The main current interests of Amylia Ait Saadi include Unmanned Aerial Vehicles, path planning, application of meta-heuristics for optimization problems, and Artificial Intelligence approaches.<\/p>\n\n\n\n<p><strong>Short biography<\/strong><\/p>\n\n\n\n<p>Amylia Ait Saadi is a PhD student in LIST Laboratory (University MHamed Bougara Boumerdes, Algeria) and LISV Laboratory (University of Paris-Saclay, France). She has a Master degree in Networks and Telecommunications from the University of Science and Technology Houari Boumediene (USTHB), Algeria that she obtained in 2019. She is currently working as an Assistant Professor at ESME engineering school, since September 2023.<\/p>\n","protected":false},"featured_media":0,"template":"","team_cat":[],"class_list":["post-6775","team","type-team","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.8 (Yoast SEO v27.3) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Amylia Ait Saadi -<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esme.fr\/recherche\/chercheur\/amylia-ait-saadi\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Amylia Ait Saadi\" \/>\n<meta property=\"og:description\" content=\"Overview of research area The main current interests of Amylia Ait Saadi include Unmanned Aerial Vehicles, path planning, application of meta-heuristics for optimization problems, and Artificial Intelligence approaches. 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