{"id":7939,"date":"2025-04-28T13:20:15","date_gmt":"2025-04-28T13:20:15","guid":{"rendered":"https:\/\/www.fondazionedare.it\/?page_id=7939"},"modified":"2025-05-05T13:31:45","modified_gmt":"2025-05-05T13:31:45","slug":"workshop-machine-learning-operations","status":"publish","type":"page","link":"https:\/\/www.fondazionedare.it\/en\/workshop-machine-learning-operations\/","title":{"rendered":"Workshop on Machine Learning Operations &#8211; MLOps25"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"7939\" class=\"elementor elementor-7939\" data-elementor-post-type=\"page\">\n\t\t\t\t<div class=\"elementor-element elementor-element-586bfb01 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-parent\" data-id=\"586bfb01\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2b3cc909 elementor-widget-divider--view-line elementor-widget elementor-widget-divider\" data-id=\"2b3cc909\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"divider.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-divider\">\n\t\t\t<span class=\"elementor-divider-separator\">\n\t\t\t\t\t\t<\/span>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-38ca23d8 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-parent\" data-id=\"38ca23d8\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-48617c38 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-child\" data-id=\"48617c38\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2eb02b61 wpr-post-info-align-center elementor-widget elementor-widget-wpr-post-info\" data-id=\"2eb02b61\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wpr-post-info.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<ul class=\"wpr-post-info wpr-post-info-vertical\"><li class=\"wpr-post-info-date\"><span>28\/04\/2025<\/span><\/li><\/ul>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-2835f95a e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-child\" data-id=\"2835f95a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-1c89a1ec wpr-post-info-align-center elementor-widget elementor-widget-wpr-post-info\" data-id=\"1c89a1ec\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"wpr-post-info.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<ul class=\"wpr-post-info wpr-post-info-vertical\"><li class=\"wpr-post-info-taxonomy\"><a href=\"https:\/\/www.fondazionedare.it\/en\/tag\/dare\/\">DARE<span class=\"tax-sep\">, <\/span><\/a><a href=\"https:\/\/www.fondazionedare.it\/en\/tag\/progetto\/\">Project<\/a><\/li><\/ul>\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-76b6fa64 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-parent\" data-id=\"76b6fa64\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t<div class=\"elementor-element elementor-element-1bfd2b9c e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-child\" data-id=\"1bfd2b9c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2cbc92da elementor-hidden-mobile elementor-widget elementor-widget-image\" data-id=\"2cbc92da\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"310\" height=\"1195\" src=\"https:\/\/www.fondazionedare.it\/wp-content\/uploads\/2024\/05\/barre_verde-primario.webp\" class=\"attachment-medium_large size-medium_large wp-image-1025\" alt=\"\" srcset=\"https:\/\/www.fondazionedare.it\/wp-content\/uploads\/2024\/05\/barre_verde-primario.webp 310w, https:\/\/www.fondazionedare.it\/wp-content\/uploads\/2024\/05\/barre_verde-primario-78x300.webp 78w, https:\/\/www.fondazionedare.it\/wp-content\/uploads\/2024\/05\/barre_verde-primario-266x1024.webp 266w, https:\/\/www.fondazionedare.it\/wp-content\/uploads\/2024\/05\/barre_verde-primario-200x771.webp 200w\" sizes=\"(max-width: 310px) 100vw, 310px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-3171251a e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-child\" data-id=\"3171251a\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-3b024432 e-con-full e-flex wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-child\" data-id=\"3b024432\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d771efb elementor-widget elementor-widget-heading\" data-id=\"d771efb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Workshop on Machine Learning Operations \u2013 MLOps25<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32d89bf elementor-widget__width-auto e-transform elementor-widget elementor-widget-text-editor\" data-id=\"32d89bf\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;_transform_translateY_effect&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:5,&quot;sizes&quot;:[]},&quot;_transform_translateX_effect&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateX_effect_widescreen&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateX_effect_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateX_effect_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateY_effect_widescreen&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateY_effect_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;_transform_translateY_effect_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]}}\" 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<p>\ud83d\udce2\u00a0Call for Papers: Workshop su MLOps \u2013 Bridging the Gap Between Models and Production.<\/p><p>In recent years, the integration of machine learning and deep learning models into real-world applications has highlighted significant operational challenges in building, deploying, monitoring, and maintaining the models.<\/p><p>\ud83d\udd0d MLOps has emerged as a key approach to address these challenges, aiming to automate, scale, and make ML workflows reproducible.<\/p><p>From October 25 to 30, 2025, MLOps25, the first ECAI Workshop on MLOps, will be held in Bologna. The DARE Foundation will be an institutional partner, with a focus on the theme of artificial intelligence for healthcare.<\/p><p>\ud83d\udcda We invite researchers, professionals, and teams to submit contributions on the following topics (and beyond):<br \/>&#8211; MLOps frameworks<br \/>&#8211; ML systems lifecycle management<br \/>&#8211; ML pipelines orchestration<br \/>&#8211; Practices to ensure ML model reproducibility, traceability, and explainability<br \/>&#8211; Continuous integration\/continuous delivery (CI\/CD) practices for ML models<br \/>&#8211; ML model monitoring and observability<br \/>&#8211; Application of MLOps principles to large language models (LLMOps)<br \/>&#8211; ML-specific architecture design and patterns<br \/>&#8211; Experience reports on real-world MLOps applications<br \/>&#8211; Challenges in applying MLOps to specific domains (e.g., healthcare and finance)<br \/>&#8211; Ethics and Accountability in MLOps<br \/>&#8211; AutoML applications in MLOps<br \/>&#8211; Collaboration and team dynamics in MLOps<br \/>&#8211; Regulatory and policy aspects of MLOps<br \/>&#8211; MLOps strategies for Green AI<br \/>&#8211; Security and data privacy in MLOps<\/p><p>\ud83d\udcc5 Paper submission deadline: <br \/>Tuesday, 20th May 2025<\/p><p>The papers must comply with the CEURART style required by the CEUR Workshop Proceedings. Authors can use the LaTeX, Word (DOCX), or LibreOffice (ODT) templates available here. <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/lnkd.in\/gNP8n2MR\" target=\"_self\" data-test-app-aware-link=\"\">https:\/\/lnkd.in\/gNP8n2MR<\/a>.<\/p><p>An Overleaf model is available here: <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/lnkd.in\/eMDfPTAs\" target=\"_self\" data-test-app-aware-link=\"\">https:\/\/lnkd.in\/eMDfPTAs<\/a><\/p><p>Please use the one-column version and make sure to use the Libertinus font as specified in the templates.<\/p><p>All papers must be submitted in \u201cdouble blind\u201d mode (authors\u2019 names must be omitted from the submission) and uploaded via the EasyChair submission site: <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/lnkd.in\/eDBfBM-Z\" target=\"_self\" data-test-app-aware-link=\"\">https:\/\/lnkd.in\/eDBfBM-Z<\/a><\/p><p>Each paper will receive at least two reviews from the program committee.<\/p><p>Event link: <a href=\"https:\/\/collab.di.uniba.it\/mlops\/\">https:\/\/collab.di.uniba.it\/mlops\/<\/a><\/p><p>We look forward to reading your contributions and participating in the stimulating discussions on MLOps that will take place during the workshop, aiming to build the foundations for increasingly robust and efficient ML operations.<\/p><p><a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23fondazionedare&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>fondazioneDARE<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23darefoundation&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>DAREfoundation<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23digitallifelongprevention&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>DIgitalLifelongPrevention<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23mlops&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>MLOps<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23callforpapers&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>CallForPapers<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23ai&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>AI<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23machinelearning&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>MachineLearning<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23deeplearning&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>DeepLearning<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23datascience&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>DataScience<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23llmops&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>LLMOps<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23greenai&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>GreenAI<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23mlinproduction&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>MLinProduction<\/a> <a class=\"nuXDIvMbeMYWApPugutCOKmVhZzvTYUM\" tabindex=\"0\" href=\"https:\/\/www.linkedin.com\/search\/results\/all\/?keywords=%23aiethics&amp;origin=HASH_TAG_FROM_FEED\" data-test-app-aware-link=\"\"><span class=\"visually-hidden\">hashtag<\/span><span aria-hidden=\"true\">#<\/span>AIethics<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\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<div class=\"elementor-element elementor-element-1e3e0659 e-flex e-con-boxed wpr-particle-no wpr-jarallax-no wpr-parallax-no wpr-sticky-section-no wpr-column-slider-no wpr-equal-height-no e-con e-parent\" data-id=\"1e3e0659\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t\t<div 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Negli ultimi anni, l\u2019integrazione dei modelli di\u00a0machine learning\u00a0e\u00a0deep learning\u00a0nelle applicazioni reali ha messo in luce sfide operative significative nella costruzione, distribuzione, monitoraggio e manutenzione dei modelli. \ud83d\udd0d\u00a0MLOps\u00a0si \u00e8 affermato come approccio chiave per affrontare queste sfide, con l\u2019obiettivo di automatizzare, rendere scalabili e riproducibili i flussi di lavoro ML. Dal 25 al 30 ottobre 2025 si terr\u00e0 a Bologna\u00a0MLOps25\u00a0il primo ECAI Workshop su MLOps\u00a0di cui la Fondazione DARE sar\u00e0 partner istituzionale con un focus sul tema dell\u2019intelligenza artificiale per la Sanit\u00e0. \ud83d\udcdaInvitiamo ricercatori, professionisti e team a inviare contributi sui seguenti temi (e oltre):&#8211; MLOps frameworks&#8211; ML systems lifecycle management&#8211; ML pipelines orchestration&#8211; Practices to ensure ML model reproducibility, traceability, and explainability&#8211; Continuous integration\/continuous delivery (CI\/CD) practices for ML models&#8211; ML model monitoring and observability&#8211; Application of MLOps principles to large language models (LLMOps)&#8211; ML-specific architecture design and patterns&#8211; Experience reports on real-world MLOps applications&#8211; Challenges in applying MLOps to specific domains (e.g., healthcare and finance)&#8211; Ethics and Accountability in MLOps&#8211; AutoML applications in MLOps&#8211; Collaboration and team dynamics in MLOps&#8211; Regulatory and policy aspects of MLOps&#8211; MLOps strategies for Green AI&#8211; Security and data privacy in MLOps \ud83d\udcc5 Scadenza per l\u2019invio dei paper: Marted\u00ec 20 maggio 2025 Gli elaborati devono rispettare lo stile CEURART richiesto dagli Atti del Workshop CEUR. Gli autori possono utilizzare i modelli LaTeX, Word (DOCX) o LibreOffice (ODT) disponibili\u00a0qui https:\/\/lnkd.in\/gNP8n2MR. Un modello Overleaf \u00e8 disponibile anche\u00a0qui https:\/\/lnkd.in\/eMDfPTAs Si prega di utilizzare la versione a 1 colonna e di assicurarsi di utilizzare il font Libertinus come specificato nei modelli. Tutti gli elaborati devono essere inviati in modalit\u00e0 &#8220;double blind&#8221; (i nomi degli autori devono essere omessi dall&#8217;invio) e caricati tramite\u00a0the EasyChair submission site: https:\/\/lnkd.in\/eDBfBM-Z Ogni elaborato ricever\u00e0 almeno due valutazioni dalla commissione del programma. Link evento: https:\/\/collab.di.uniba.it\/mlops\/ Attendiamo di leggere i vostri contributi e di partecipare alle stimolanti discussioni sulle MLOps che si terranno durante il workshop per costruire le basi per un&#8217;operativit\u00e0 ML sempre pi\u00f9 robusta ed efficiente. hashtag#fondazioneDARE hashtag#DAREfoundation hashtag#DIgitalLifelongPrevention hashtag#MLOps hashtag#CallForPapers hashtag#AI hashtag#MachineLearning hashtag#DeepLearning hashtag#DataScience hashtag#LLMOps hashtag#GreenAI hashtag#MLinProduction hashtag#AIethics Articolo precedenteArticolo successivo torna su<\/p>","protected":false},"author":2,"featured_media":8020,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[4,22],"tags":[5,17],"class_list":["post-7939","page","type-page","status-publish","has-post-thumbnail","hentry","category-all-news","category-opportunita","tag-dare","tag-progetto"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Workshop on Machine Learning Operations - MLOps25 - Fondazione DARE<\/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.fondazionedare.it\/en\/workshop-machine-learning-operations\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Workshop on Machine Learning Operations - MLOps25 - Fondazione DARE\" \/>\n<meta property=\"og:description\" content=\"Aprile 28, 2025 DARE, Progetto Workshop on Machine Learning Operations \u2013 MLOps25 \ud83d\udce2\u00a0Call for Papers: Workshop su MLOps \u2013 Bridging the Gap Between Models and Production. Negli ultimi anni, l\u2019integrazione dei modelli di\u00a0machine learning\u00a0e\u00a0deep learning\u00a0nelle applicazioni reali ha messo in luce sfide operative significative nella costruzione, distribuzione, monitoraggio e manutenzione dei modelli. \ud83d\udd0d\u00a0MLOps\u00a0si \u00e8 affermato come approccio chiave per affrontare queste sfide, con l\u2019obiettivo di automatizzare, rendere scalabili e riproducibili i flussi di lavoro ML. Dal 25 al 30 ottobre 2025 si terr\u00e0 a Bologna\u00a0MLOps25\u00a0il primo ECAI Workshop su MLOps\u00a0di cui la Fondazione DARE sar\u00e0 partner istituzionale con un focus sul tema dell\u2019intelligenza artificiale per la Sanit\u00e0. \ud83d\udcdaInvitiamo ricercatori, professionisti e team a inviare contributi sui seguenti temi (e oltre):&#8211; MLOps frameworks&#8211; ML systems lifecycle management&#8211; ML pipelines orchestration&#8211; Practices to ensure ML model reproducibility, traceability, and explainability&#8211; Continuous integration\/continuous delivery (CI\/CD) practices for ML models&#8211; ML model monitoring and observability&#8211; Application of MLOps principles to large language models (LLMOps)&#8211; ML-specific architecture design and patterns&#8211; Experience reports on real-world MLOps applications&#8211; Challenges in applying MLOps to specific domains (e.g., healthcare and finance)&#8211; Ethics and Accountability in MLOps&#8211; AutoML applications in MLOps&#8211; Collaboration and team dynamics in MLOps&#8211; Regulatory and policy aspects of MLOps&#8211; MLOps strategies for Green AI&#8211; Security and data privacy in MLOps \ud83d\udcc5 Scadenza per l\u2019invio dei paper: Marted\u00ec 20 maggio 2025 Gli elaborati devono rispettare lo stile CEURART richiesto dagli Atti del Workshop CEUR. Gli autori possono utilizzare i modelli LaTeX, Word (DOCX) o LibreOffice (ODT) disponibili\u00a0qui https:\/\/lnkd.in\/gNP8n2MR. Un modello Overleaf \u00e8 disponibile anche\u00a0qui https:\/\/lnkd.in\/eMDfPTAs Si prega di utilizzare la versione a 1 colonna e di assicurarsi di utilizzare il font Libertinus come specificato nei modelli. Tutti gli elaborati devono essere inviati in modalit\u00e0 &#8220;double blind&#8221; (i nomi degli autori devono essere omessi dall&#8217;invio) e caricati tramite\u00a0the EasyChair submission site: https:\/\/lnkd.in\/eDBfBM-Z Ogni elaborato ricever\u00e0 almeno due valutazioni dalla commissione del programma. 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Dal 25 al 30 ottobre 2025 si terr\u00e0 a Bologna\u00a0MLOps25\u00a0il primo ECAI Workshop su MLOps\u00a0di cui la Fondazione DARE sar\u00e0 partner istituzionale con un focus sul tema dell\u2019intelligenza artificiale per la Sanit\u00e0. \ud83d\udcdaInvitiamo ricercatori, professionisti e team a inviare contributi sui seguenti temi (e oltre):&#8211; MLOps frameworks&#8211; ML systems lifecycle management&#8211; ML pipelines orchestration&#8211; Practices to ensure ML model reproducibility, traceability, and explainability&#8211; Continuous integration\/continuous delivery (CI\/CD) practices for ML models&#8211; ML model monitoring and observability&#8211; Application of MLOps principles to large language models (LLMOps)&#8211; ML-specific architecture design and patterns&#8211; Experience reports on real-world MLOps applications&#8211; Challenges in applying MLOps to specific domains (e.g., healthcare and finance)&#8211; Ethics and Accountability in MLOps&#8211; AutoML applications in MLOps&#8211; Collaboration and team dynamics in MLOps&#8211; Regulatory and policy aspects of MLOps&#8211; MLOps strategies for Green AI&#8211; Security and data privacy in MLOps \ud83d\udcc5 Scadenza per l\u2019invio dei paper: Marted\u00ec 20 maggio 2025 Gli elaborati devono rispettare lo stile CEURART richiesto dagli Atti del Workshop CEUR. Gli autori possono utilizzare i modelli LaTeX, Word (DOCX) o LibreOffice (ODT) disponibili\u00a0qui https:\/\/lnkd.in\/gNP8n2MR. Un modello Overleaf \u00e8 disponibile anche\u00a0qui https:\/\/lnkd.in\/eMDfPTAs Si prega di utilizzare la versione a 1 colonna e di assicurarsi di utilizzare il font Libertinus come specificato nei modelli. Tutti gli elaborati devono essere inviati in modalit\u00e0 &#8220;double blind&#8221; (i nomi degli autori devono essere omessi dall&#8217;invio) e caricati tramite\u00a0the EasyChair submission site: https:\/\/lnkd.in\/eDBfBM-Z Ogni elaborato ricever\u00e0 almeno due valutazioni dalla commissione del programma. 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