{"id":58,"date":"2019-03-26T08:08:27","date_gmt":"2019-03-26T07:08:27","guid":{"rendered":"http:\/\/www.labdma.unina.it\/?page_id=58"},"modified":"2026-03-03T16:12:17","modified_gmt":"2026-03-03T15:12:17","slug":"projects","status":"publish","type":"page","link":"https:\/\/www.labdma.unina.it\/index.php\/projects\/","title":{"rendered":"Projects"},"content":{"rendered":"\n<style>\n.projects-container{\n  display:grid;\n  grid-template-columns:repeat(auto-fit,minmax(450px,1fr));\n  gap:30px;\n  margin:40px 0;\n}\n.project-card{\n  background:#fff;\n  border-radius:12px;\n  padding:25px;\n  box-shadow:0 4px 15px rgba(0,0,0,.08);\n  transition:transform .2s ease;\n}\n.project-card:hover{ transform:translateY(-5px); }\n\n.project-header{\n  display:flex;\n  align-items:center;\n  gap:15px;\n  margin-bottom:12px;\n}\n.project-logo{\n  width:60px;\n  height:60px;\n  object-fit:contain;\n  flex:0 0 auto;\n}\n\/* Se non c'\u00e8 logo, puoi semplicemente NON mettere il div .project-logo-wrap *\/\n.project-title{\n  font-size:20px;\n  font-weight:700;\n  color:#1e2a38;\n  margin:0;\n}\n.project-meta{\n  font-size:14px;\n  font-weight:600;\n  color:#6c757d;\n  margin-top:6px;\n}\n.project-tech{\n  font-size:13px;\n  color:#8a8a8a;\n  font-style:italic;\n  margin:10px 0 12px 0;\n  min-height:18px; \/* mantiene una riga \"vuota\" anche se lasci il contenuto vuoto *\/\n}\n.project-description{\n  font-size:15px;\n  line-height:1.6;\n  color:#333;\n}\n\n.project-card--wide {\n  grid-column: span 2;\n}\n\n.project-columns {\n  display: flex;\n  gap: 40px;\n  margin-top: 15px;\n}\n\n.project-columns div {\n  flex: 1;\n}\n\n<\/style>\n\n<div class=\"projects-container\">\n\n\n    <!-- FLINT -->\n<div class=\"project-card\">\n  <div class=\"project-header\">\n    <!-- Logo opzionale -->\n    <!-- <img decoding=\"async\" src=\"images\/flint-logo.png\" alt=\"FLINT logo\" class=\"project-logo\"> -->\n    <div>\n      <div class=\"project-title\">\n        FLINT \u2013 Federated Learning for INdustrial Twins\n      <\/div>\n      <div class=\"project-meta\">\n        MIMIT \u2013 Duration: 36 months &#8211; Starting Date: February 1st, 2026\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"project-tech\">\n    CUP: ______ | Proposal Code: ______ | TRL Target: 7\n  <\/div>\n\n  <div class=\"project-description\">\n    FLINT develops a federated, edge-based platform integrating Federated Learning and Digital Twins for privacy-preserving AI in critical sectors such as advanced manufacturing, energy systems and healthcare. The architecture enables distributed model training without data centralisation, ensuring security, energy efficiency and operational resilience. The project aims to reach TRL 7 through real-world validation, including industrial environments and demonstrators (e.g., ENEA).\n  <\/div>\n<\/div>\n\n\n\n    <!-- ECHO -->\n<div class=\"project-card\">\n  <div class=\"project-header\">\n    <!-- Logo opzionale -->\n    <!-- <img decoding=\"async\" src=\"images\/echo-logo.png\" alt=\"ECHO-TWIN logo\" class=\"project-logo\"> -->\n    <div>\n      <div class=\"project-title\">\n        ECHO-TWIN \u2013 Edge-Cloud-HPC Optimised Twins\n      <\/div>\n      <div class=\"project-meta\">\n       PN RIC 2021\u20132027 \u2013 ICSC National Research Centre &#8211; &#8211; Starting Date: May 1st, 2026\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"project-tech\">\n    Proposal Code: MI 701 | Actions: 1.1.2 \/ 1.1.3b \/ 1.4.3 |\n  <\/div>\n\n  <div class=\"project-description\">\n    ECHO-TWIN builds an integrated Edge\u2013Cloud\u2013HPC ecosystem for Digital Twin-enabled Smart Ecosystems across strategic domains such as health, climate, mobility and AI. The programme combines research (ECHO-TWIN-RISE), infrastructure federation and innovation hubs (ECHO-TWIN-NET), and advanced skills development (ECHO-TWIN-UP). It strengthens HPC and AI infrastructures in Southern Italy while promoting sustainable, DNSH-compliant digital innovation and technology transfer to SMEs.\n  <\/div>\n<\/div>\n\n\n\n<!-- TUAI \u2013 Double Width Card (more detailed) -->\n<div class=\"project-card project-card--wide\">\n\n  <div class=\"project-header\">\n    <!-- Logo opzionale -->\n    <!-- <img decoding=\"async\" src=\"images\/tuai-logo.png\" alt=\"TUAI logo\" class=\"project-logo\"> -->\n    <div>\n      <div class=\"project-title\">\n        TUAI \u2013 Towards an Understanding of Artificial Intelligence via a Transparent, Open &#038; Explainable Perspective\n      <\/div>\n      <div class=\"project-meta\">\n        Horizon Europe \u2013 MSCA Doctoral Networks (HORIZON-MSCA-2023-DN-01) | Project No: 101168344\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"project-tech\">\n    Oct 2024 \u2013 Sept 2028 (48 months) | Total budget: \u20ac3,358,980 | 13 Doctoral Candidates (DCs) <br>\n    Granting Authority: REA | Coordinator: SUT (Politechnika Slaska, PL) | UNINA: Beneficiary\n  <\/div>\n\n  <div class=\"project-description\">\n\n    <p>\n      TUAI delivers high-quality doctoral training on <strong>sustainable and trustworthy AI<\/strong> for\n      <strong>smart manufacturing, smart cities, smart healthcare, and smart mobility<\/strong>. The network combines\n      academic excellence with strong non-academic exposure to prepare creative, entrepreneurial researchers able to\n      develop AI that is <strong>transparent, explainable, robust and environmentally aware<\/strong>.\n    <\/p>\n\n    <div class=\"project-columns\">\n      <div>\n        <h4>Research Areas (RAs)<\/h4>\n        <ul>\n          <li><strong>Time Series Analysis<\/strong> for real-world predictive services<\/li>\n          <li><strong>Sensor Fusion<\/strong> for multimodal intelligent systems<\/li>\n          <li><strong>Federated Learning<\/strong> for privacy-preserving distributed intelligence<\/li>\n          <li><strong>Sustainability &#038; Trustworthiness<\/strong> (explainability, robustness, transparency)<\/li>\n        <\/ul>\n      <\/div>\n\n      <div>\n        <h4>Training Approach<\/h4>\n        <ul>\n          <li>Network-wide training activities and joint events<\/li>\n          <li>Intersectoral <strong>secondments<\/strong> (academia\u2013industry)<\/li>\n          <li>Research + transferable skills (innovation, entrepreneurship)<\/li>\n          <li>Holistic training across all RAs (intertwined DC projects)<\/li>\n        <\/ul>\n      <\/div>\n    <\/div>\n\n    <h4 style=\"margin-top:14px;\">Consortium<\/h4>\n    <p style=\"margin:6px 0 0 0;\">\n      <strong>Beneficiaries:<\/strong> SUT (PL), UNINA (IT), UPM (ES), NTNU (NO), UNIOVI (ES), HVL (NO).<br>\n      <strong>Associated Partners (industry &#038; research):<\/strong> CONFORM (IT), ALMAWAVE (IT), AIUT (PL),\n      Continental\/CONTI (DE), GMV (ES), BIOKERALTY (ES), TheNextPangea (ES), NORSK REGNESENTRAL (NO).\n    <\/p>\n\n    <h4 style=\"margin-top:14px;\">Expected Impact<\/h4>\n    <ul style=\"margin-top:6px;\">\n      <li>Advanced AI methods for smart services that are both <strong>human- and environment-centered<\/strong><\/li>\n      <li>Privacy-preserving ML (e.g., federated learning) and reliable AI pipelines<\/li>\n      <li>New highly skilled researchers for academic and non-academic careers across Europe<\/li>\n    <\/ul>\n\n  <\/div>\n\n<\/div>\n\n\n\n<!-- AIFEMO -->\n<div class=\"project-card\">\n  <div class=\"project-header\">\n    <!-- Logo opzionale -->\n    <!-- <img decoding=\"async\" src=\"images\/aifemo-logo.png\" alt=\"AIFEMO logo\" class=\"project-logo\"> -->\n    <div>\n      <div class=\"project-title\">AIFEMO \u2013 AI-Optimized Fuel Efficiency in Maritime Operations<\/div>\n      <div class=\"project-meta\">ICSC (Spoke 9) \u2013 Proponent: Univ. of Naples Federico II (DMA)<\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"project-tech\">CUP: ______ | Project code: ______ | Duration: 18 months | TRL: 3 \u2192 6\u20137<\/div>\n\n  <div class=\"project-description\">\n    AIFEMO develops an AI framework for fuel-efficient maritime operations, focusing on optimal routing (weather routing) and operational settings to reduce fuel consumption and emissions. The project relies on simulation-based validation (CETENA simulator) and leverages ICSC\/CINECA GPU computing resources for model training and optimization, aiming at a functional prototype validated in realistic scenarios.\n  <\/div>\n<\/div>\n<!-- Source: :contentReference[oaicite:0]{index=0} -->\n\n<!-- SESG -->\n<div class=\"project-card\">\n  <div class=\"project-header\">\n    <!-- Logo opzionale -->\n    <!-- <img decoding=\"async\" src=\"images\/sesg-logo.png\" alt=\"SESG logo\" class=\"project-logo\"> -->\n    <div>\n      <div class=\"project-title\">\n        SESG \u2013 Integrated Platform for Enhanced Analysis of Environmental, Social, and Governance Reports\n      <\/div>\n      <div class=\"project-meta\">\n        ICSC \u2013 Spoke 9 | April 2024 \u2013 December 2025\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div class=\"project-tech\">\n   Public Partners: UniSalento, UniBO, UniNA | Private Partners: IFAB\n  <\/div>\n\n  <div class=\"project-description\">\n    SESG develops an advanced AI-driven platform for the structured analysis of ESG (Environmental, Social and Governance) data extracted from non-financial reports (DNF). Leveraging state-of-the-art analytics, Natural Language Processing (NLP) and Large Language Models (LLMs), the project enables automated extraction and validation of quantitative and qualitative ESG KPIs, facilitating benchmarking and informed decision-making. \n\n  <\/div>\n<\/div>\n\n\n\n  <!-- G.A.N.D.A.L.F -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale: se non c'\u00e8, elimina <img ...> -->\n   <!--   <img decoding=\"async\" src=\"images\/gandalf-logo.png\" alt=\"GANDALF logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">G.A.N.D.A.L.F \u2013 Gan Approaches for Non-iiD Aiding Learning in Federations<\/div>\n        <div class=\"project-meta\">PRIN 2022 \u2013 Principal Investigator: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | Grant\/Project ID: ______ | Funding body: ______<\/div>\n    <div class=\"project-description\">\n      The project tackles the non-IID challenge in Federated Learning, improving robustness and performance in decentralized and Edge-AI settings. It combines GAN-based strategies with a blockchain layer to mitigate data integrity and security attacks.\n    <\/div>\n  <\/div>\n\n  <!-- D.I.R.E.C.T.I.O.N.S. -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/directions-logo.png\" alt=\"DIRECTIONS logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">D.I.R.E.C.T.I.O.N.S. \u2013 Deep learning aIded foReshock deteCTIOn Of iNduced mainShocks<\/div>\n        <div class=\"project-meta\">PRIN PNRR 2022 \u2013 Research Unit Coordinator: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | Project code: ______ | Funding line: ______<\/div>\n    <div class=\"project-description\">\n      Deep learning methods to detect foreshocks related to induced seismicity in geothermal\/energy operations. The project aims to reduce subjectivity in analysis by learning predictive patterns from seismic evolution during field activities.\n    <\/div>\n  <\/div>\n\n  <!-- C.L.A.I.M. -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/claim-logo.png\" alt=\"CLAIM logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">C.L.A.I.M. \u2013 Artificial Intelligence for Competences and Learning<\/div>\n        <div class=\"project-meta\">Erasmus+ KA220-VET (EU), 2023\u20132025 \u2013 Principal Investigator: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">Grant Agreement: ______ | Call\/Action: KA220-VET | Partners: ______<\/div>\n    <div class=\"project-description\">\n      AI-driven, competence-based tools for SMEs to assess skills and tailor training to real needs. The project supports digital transition and sustainability through personalized learning paths instead of generic training.\n    <\/div>\n  <\/div>\n\n  <!-- Dutch Polymer Institute -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/dpi-logo.png\" alt=\"DPI logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">Deep-Learning-aided GPC-IR fingerprinting of complex polyolefin mixtures<\/div>\n        <div class=\"project-meta\">2022 Call for Research Proposals \u2013 Dutch Polymer Institute \u2013 PI\/Applicant: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">Project ID: ______ | Funding body: Dutch Polymer Institute | Call year: 2022<\/div>\n    <div class=\"project-description\">\n      An interdisciplinary approach to improve mechanical recycling of polyolefin waste via rapid fine sorting. It integrates high-end GPC-IR characterization with AI models trained on molecular fingerprint archives to identify complex mixtures.\n    <\/div>\n  <\/div>\n\n  <!-- ELIXIRxNextGenIT -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/elixir-logo.png\" alt=\"ELIXIR logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">ELIXIR x NextGenerationIT \u2013 Consolidamento dell\u2019Infrastruttura Italiana per i Dati Omici e la Bioinformatica<\/div>\n        <div class=\"project-meta\">PNRR \u2013 Avviso n. 3264 del 28\/12\/2021 \u2013 Research Unit Coordinator: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | Avviso: 3264 (28\/12\/2021) | Workpackage\/Node: ______<\/div>\n    <div class=\"project-description\">\n      Strengthening the Italian ELIXIR node by consolidating services and infrastructure for bioinformatics and integrative omics. The project provides advanced platforms for high-throughput generation and analysis of genomic, proteomic and metabolomic data.\n    <\/div>\n  <\/div>\n\n  <!-- 4.I. -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/4i-logo.png\" alt=\"4I logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">4.I. \u2013 mixed reality, machine learning, gamification and educational for Industry<\/div>\n        <div class=\"project-meta\">M.I.S.E. Prog. n. F\/190130\/02\/X44 \u2013 PI: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | Prog.: F\/190130\/02\/X44 | POR\/PON line: ______<\/div>\n    <div class=\"project-description\">\n      A new industrial model for knowledge sharing, process supervision, maintenance, training and QA. It leverages mixed reality, machine learning, educational technologies and gamification to improve operational effectiveness.\n    <\/div>\n  <\/div>\n\n  <!-- BIOCHIP -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/biochip-logo.png\" alt=\"BIOCHIP logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">BIOCHIP \u2013 Intelligent biosensors based on chimeric proteins<\/div>\n        <div class=\"project-meta\">FRA 2020 \u2013 Research Unit Coordinator: Prof. Salvatore Cuomo<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | FRA call: 2020 | Host institution: ______<\/div>\n    <div class=\"project-description\">\n      Intelligent biosensors designed by combining biochemistry, chemistry and informatics for high sensitivity and reliability across diverse matrices. Chimeric proteins are engineered for monitoring analytes relevant to diagnostics and food safety.\n    <\/div>\n  <\/div>\n\n  <!-- C.E.T.R.A. -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/cetra-logo.png\" alt=\"CETRA logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">C.E.T.R.A. \u2013 Cultural Equipment with Transmedial Recommendation Analytics<\/div>\n        <div class=\"project-meta\">POR FESR Campania 2014\/2020 O.S. 1.1 \u2013 PI: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | POR FESR 2014\/2020 | Phase: ______ (F1\/F2)<\/div>\n    <div class=\"project-description\">\n      A transmedial ecosystem combining IoT, machine learning, recommender systems, content adaptivity and Big Data analytics. It targets tourism and cultural processes across both permanent sites (museums) and itinerant\/episodic events.\n    <\/div>\n  <\/div>\n\n  <!-- Energy efficiency models -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/energy-models-logo.png\" alt=\"Energy models logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">Modelli matematici per l\u2019efficientamento energetico degli edifici<\/div>\n        <div class=\"project-meta\">PON Ricerca e Innovazione 2014\u20132020<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | PON line: ______ | Partner institutions: ______<\/div>\n    <div class=\"project-description\">\n      Research on PDE-based mathematical models for heat conduction, diffusion and radiation to optimize thermal insulation. The work supports energy-efficient building design and sustainable materials placement strategies.\n    <\/div>\n  <\/div>\n\n  <!-- CUP-i-One -->\n  <div class=\"project-card\">\n    <div class=\"project-header\">\n      <!-- Logo opzionale -->\n      <!-- <img decoding=\"async\" src=\"images\/cupione-logo.png\" alt=\"CUP-i-One logo\" class=\"project-logo\"> -->\n      <div>\n        <div class=\"project-title\">CUP-i-One \u2013 CUP in un Click (in collaborazione con il CINI)<\/div>\n        <div class=\"project-meta\">POR FESR Campania 2014\/2020 O.S. 1.1 \u2013 Research Unit Coordinator: Prof. Francesco Piccialli<\/div>\n      <\/div>\n    <\/div>\n    <div class=\"project-tech\">CUP: ______ | Project code: ______ | Compliance: GDPR \/ LEA \/ eHealth Strategy<\/div>\n    <div class=\"project-description\">\n      Evolution of the healthcare booking platform (CUP) through system integration and interoperability standards. The project adds advanced analytics and KPI-based decision support while ensuring GDPR compliance and alignment with national eHealth guidelines.\n    <\/div>\n  <\/div>\n\n<\/div>\n\n\n\n<p><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<div class=\"slide-text-bg2\">\n<h3>&lt;div class=&quot;slide-text-bg2&quot;&gt;<br \/>\n&lt;h3&gt;FLINT \u2013 Federated Learning for INdustrial Twins MIMIT \u2013 Duration: 36 months &#8211; Starting Date: February 1st, 2026 CUP: ______&lt;\/h3&gt;<br \/>\n&lt;\/div&gt;<br \/>\n&lt;div class=&quot;flex-btn-div&quot;&gt;&lt;a href=&quot;https:\/\/www.labdma.unina.it\/index.php\/projects\/&quot; class=&quot;btn1 flex-btn&quot;&gt;Leggi tutto&lt;\/a&gt;&lt;\/div&gt;<br \/>\n<\/h3>\n<\/div>\n<div class=\"flex-btn-div\"><a href=\"https:\/\/www.labdma.unina.it\/index.php\/projects\/\" class=\"btn1 flex-btn\">Leggi tutto<\/a><\/div>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/pages\/58"}],"collection":[{"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/comments?post=58"}],"version-history":[{"count":42,"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/pages\/58\/revisions"}],"predecessor-version":[{"id":1670,"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/pages\/58\/revisions\/1670"}],"wp:attachment":[{"href":"https:\/\/www.labdma.unina.it\/index.php\/wp-json\/wp\/v2\/media?parent=58"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}