BEGIN:VCALENDAR VERSION:2.0 PRODID:-//CERN//INDICO//EN BEGIN:VEVENT SUMMARY:Caffè Scientifico di Agraria 2026 DTSTART;VALUE=DATE-TIME:20260304T133000Z DTEND;VALUE=DATE-TIME:20261209T150000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-114@cern.ch DESCRIPTION:https://indico.unina.it/event/114/ LOCATION:Dipartimento di Agraria\, Sala Cinese - Dipartimento di Medicina veterinaria e produzioni animali\, Aula Magna URL:https://indico.unina.it/event/114/ END:VEVENT BEGIN:VEVENT SUMMARY:Advanced Statistical Modeling for Sustainable Finance (ASMSF) DTSTART;VALUE=DATE-TIME:20260907T060000Z DTEND;VALUE=DATE-TIME:20260911T215900Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-116@cern.ch DESCRIPTION:Speakers: Maria Iannario (University of Naples Federico II)\nC omposition Partnership\n\n\n Università degli Studi di Napoli Federico II \, Italy (Coordinator and Host Institution)\n Athens University of Economi cs and Business\, Greece (Sending Institution)\n Technische Universität D ortmund\, Germany (Sending Institution)\n University of Twente\, The Nethe rlands (Sending Institution)\n University College Dublin\, Ireland (Sendin g Institution)\n University of Economics in Bratislava\, Slovakia (Sending Institution)\n Babeș-Bolyai University\, Cluj-Napoca\, Romania (Sending Institution)\n\n\nTopic of the program\n\nThis program provides advanced training in statistical and machine learning techniques for sustainable fi nance. A key component is the Hybrid Approach for the Analysis of Complex Data Structures\, where participants will learn to combine traditional sta tistical methods with modern computational tools to address sustainability -related financial challenges.\n\nThe course focuses on the integration of Environmental\, Social\, and Governance (ESG) factors into financial deci sion-making\, risk management\, and investment strategies. Participants wi ll explore hybrid methods to analyze complex data from various sources\, i ncluding ESG metrics\, financial time series\, and corporate reports\, usi ng tools like R and Python.\n\nLearning Outcomes\n\nBy the end of the prog ram\, participants will:\n\n\n \n Apply hybrid approaches to analyze compl ex data structures in sustainable finance.\n \n \n Build statistical and m achine learning models to assess ESG factors and their financial implicati ons.\n \n \n Understand and integrate sustainability metrics into financia l decision-making.\n \n \n Perform advanced data wrangling\, cleaning\, an d analysis for financial datasets.\n \n \n Utilize dashboards and reportin g frameworks to present actionable insights.\n \n\n\nSchedule description\ n\n1- Description of the physical component\n\nDates: 07.09.2026 to 11.09. 2026\nLocation: Naples\, University of Naples Federico II\n\n \n\nStructu re:\n\n \n\nSeptember 7\, 2026\n\n09:30–10:00 – Welcome Addresses by Institutional Representatives and Introduction to the Training School – Maria Iannario\n\n10:00–17:00\n\n      Sustainable Finance: Spatial S tatistics and Machine Learning for Climate and ESG Risk [1]\n\nInstructors :\n\n      Adriano Morales\, University of Twente\, The Netherlands\n\n       Abdulaziz Yusuf Ali\, University of Twente\, The Netherlands\n\nS hort description\n\nThis course introduces participants to sustainable fin ance through the lens of spatial data\, spatial statistics\, and machine l earning. It begins with an overview of climate finance and spatial finance \, emphasizing how asset locations\, environmental hazards\, and geospatia l information can be combined to assess physical and transition risks. Par ticipants will then explore key spatial statistical methods\, including ge ostatistics\, Bayesian modelling\, and spatial point processes\, with appl ications to housing prices and climate risk\, deforestation and asset expo sure\, hazard-related losses\, and transport emissions.\n\nMaterials > Dow nload    \n\n--------------------------------------------------------- --------------------\n\nSeptember 8\, 2026\n\n10:00–17:00\n\n      Su stainable Finance: Spatial Statistics and Machine Learning for Climate and ESG Risk [2]\n\nInstructors:\n\nAdriano Morales\, University of Twente\, The Netherlands\n\nAbdulaziz Yusuf Ali\, University of Twente\, The Nethe rlands\n\nShort description\n\nThe second part of the course focuses on ES G and financial materiality\, showing how spatial data can support the ide ntification\, measurement\, and interpretation of financially relevant sus tainability risks. Machine learning methods for spatial classification and clustering will also be introduced\, with examples related to deforestati on and mining mapping\, rooftop damage classification\, environmental risk mapping\, and broader asset-level exposure assessment. The course combine s conceptual lectures with hands-on laboratory sessions in which participa nts apply spatial and machine learning tools to develop risk maps and clas sification outputs.\n\nEvening session\n\nLaboratory lectures – supervis ed tutorial\, individual and team work.\n\nMaterials > Download       \n\n-------------------------------------------------------------------- ---------\n\nSeptember 9\, 2026     \n\n09:00 – 10:30: Latent Variab le Models for Sustainable Finance\n\nInstructor:\nMaria Iannario\, Univers ity of Naples Federico II\, Italy.\nRosa Fabbricatore\, University of Napl es Federico II\, Italy.\nMaterials > Download      \n\n \n\n11:00 – 13:00  Sustainability Analytics and Carbon Footprint Estimation in S ports \n\nInstructor:\n\nProfessor Ioannis Ntzoufras\, Department of Stat istics\, Athens University of Economics and Business\, Greece\n\nShort des cription\n\nThis lecture introduces the fundamental principles and methods for analysing survey data in the context of sports sustainability. Using data collected from spectators attending a match between the Greek Nationa l Football Team and the National Team of Ireland\, participants will explo re how survey analytics can be used to understand mobility patterns\, tran sportation choices\, and environmental attitudes among football fans.\n\nT he course demonstrates how survey data can provide valuable insights into spectator behaviour and its environmental impact. Particular emphasis will be placed on estimating the carbon footprint associated with match attend ance\, with a focus on travel-related emissions and the role of sustainabl e mobility practices.\n\nAll analyses will be conducted using R. Starting from descriptive and exploratory analytics\, participants will learn how t o summarise and visualise fans’ attitudes towards sustainability\, ident ify key mobility trends\, and quantify the environmental impact of spectat or travel. The course will then progress to more advanced analytical appro aches for estimating the overall carbon footprint of the event and assessi ng factors associated with environmentally responsible behaviours.\n\nBy t he end of the lecture\, participants will have gained practical experience in managing and analysing survey data\, interpreting sustainability-relat ed indicators\, and producing evidence-based assessments of the environmen tal impact of major sporting events.\n\nEvening session\n\nLaboratory lect ures – supervised tutorial\, individual and team work.\n\nMaterials > Do wnload      \n\n---------------------------------------------------- -------------------------\n\nSeptember 10\, 2026\n\n10:00–17:00\n\nMetho ds for Dimension Reduction and Clustering for ESG Analysis\n\nInstructor:\ n\nDimitris Karlis\, Athens University of Economics and Business\, Greece\ n\nShort description\n\nThis course introduces the basic ideas and princip les of dimension reduction. It focuses on Principal Components Analysis\, including the underlying methodology\, the choice of the number of compone nts\, variants of the method\, and applications with real data.\n\nEvening session\n\nLaboratory lectures – supervised tutorial\, individual and t eam work.\n\nMaterials > Download    \n\n \n\n----------------------- ------------------------------------------------------\n\nSeptember 11\, 2 026\n\n10:00–17:00\n\n       Machine Learning and AI in Sustainable Finance\n\nInstructor:\n\nAssociate Professor Liana Stanca\, Babeș-Bolyai University / FinTech LivingLab\n\nShort description\n\nThis lecture intro duces the fundamental principles and practical methods of applying Machine Learning and Artificial Intelligence in the context of sustainable financ e and ESG-driven decision-making. Using real-world financial and sustainab ility datasets\, participants will explore how data-driven approaches can be used to understand ESG performance\, climate risk exposure\, and sustai nability-related financial indicators across firms and markets.\n\nThe cou rse demonstrates how machine learning models and visual analytics can supp ort evidence-based sustainability assessment in finance. Particular emphas is is placed on the integration of predictive modelling and interactive da ta visualization for ESG analysis\, including the development of dynamic d ashboards for exploring sustainability metrics\, carbon exposure\, and fin ancial performance relationships.\n\nAll analyses will be conducted in R/S hiny or Python\, depending on the implementation\, combining exploratory d ata analysis\, machine learning techniques\, and interactive visualization tools such as Shiny\, Plotly\, or Dash. Starting from descriptive analyti cs and data visualization\, participants will learn how to summarize and i nterpret ESG indicators\, identify sustainability patterns across firms\, and visualize key financial and environmental relationships through intera ctive dashboards.\n\nThe course then progresses toward supervised and unsu pervised learning methods for ESG risk classification\, sustainability pro filing of companies\, and clustering of firms based on environmental and g overnance characteristics. A dedicated component is included on explainabl e AI techniques to ensure transparency and interpretability of machine lea rning outputs in financial decision contexts.\n\nBy the end of the lecture \, participants will have gained hands-on experience in building and inter preting machine learning models for sustainable finance\, designing intera ctive dashboards for ESG data exploration\, and producing data-driven insi ghts that support sustainable investment and risk assessment decisions.\n\ nEvening session\n\nLaboratory lectures – supervised tutorial\, individu al and team work.\n\nMaterials > Download      \n\n \n\nb. Descript ion of the virtual component \n\nThe programme includes online sessions d elivered via Microsoft Teams. These virtual meetings will be used for lect ures\, discussions\, supervision\, and interaction with participants.\n\nL ink to the virtual sessions: Microsoft Teams classroom \n\n \n\nStructu re:\n\nAugust 26\, 2026\n\n\n \n 10:00 CEST– Welcome and introductions b y the academic partners to greet the students\n \n 10:20–12:00 CEST– Lecture: Hybrid Data Analysis for Sustainability\n\n\nThis lecture introd uces the concept of hybrid data analysis in the context of sustainability- related decision-making. It explores how quantitative and qualitative data \, structured and unstructured information\, and different analytical appr oaches can be combined to address complex environmental\, social\, and eco nomic challenges. Participants will gain insight into key sustainability d ata sources\, common methodological approaches\, and the role of expert kn owledge in hybrid analytical frameworks.    \n\nMaterials > Download\n\n Marcos R. Machado\, University of Twente\, The Netherlands\n\n \n\nSeptem ber 2\, 2026\n\n\n 10:00–12:00 CEST– Lecture: Data Preprocessing Treat ment & Applications in Sustainability\n\n\nThis course provides an introdu ction to the theoretical foundations and practical applications of data pr eprocessing in data mining and analytics. Participants will examine the ma in stages of preprocessing\, including data cleaning\, transformation\, re duction\, and other preparation techniques that enhance the quality and us ability of data for subsequent analysis. The course also explores differen t categories of preprocessing methods and demonstrates their implementatio n through Python and Jupyter Notebooks. A sustainability-related applicati on case is included to illustrate how preprocessing techniques can be appl ied in practice to support meaningful and robust data-driven insights. \n\ nMaterials > Download\n\nMarcos R. Machado\, University of Twente\, The Ne therlands\n\nWouter van Heeswijk\, University of Twente\, The Netherlands\ n\n \n\nSeptember 25\, 2026\n\n\n 10:00–12:00 CEST– Lecture: Quarto for Reproducible Documents and Dashboards with R\n\n\nMaterials > Download \n\nAlfonso Iodice D’Enza University of Naples Federico II\, Italy\n\n\n Key Features\n\n\n Level: Master’s and PhD students.\n ECTS: 3\n Languag e: English\n Online Support: Weekly mentorship from sustainability and fin ance experts.\n\n\nHybrid Approach for Complex Data Structures\n\nThis cou rse focuses on blending traditional statistical approaches (e.g.\, regress ion\, dimension reduction) with machine learning and AI methods (e.g.\, cl ustering\, predictive analytics) to address the multifaceted challenges in sustainable finance. Emphasis is placed on handling large-scale\, heterog eneous datasets\, developing scalable models\, and deriving actionable ins ights for ESG evaluation and decision-making.\n\n \n\nPractical informati on\n\n- Level of students: Master and PhD students\n\n- Number of ECTS: 3  \n\n- Main language of instruction/training: English\n\n- Venue of Activ ities (City\, Institution): Naples\, Department of Political Sciences\, Un iversity of Naples Federico II (Statistics Laboratory and G4 room)\n\n\n\n In addition\, a tutor will be available for each participant during the tr aining period and a dedicated programme manager provided by BIP Faculty wi ll be available virtually. These figures will act as support in the learni ng and skills development phase.\n\n \n\nSocial Event Session: Guided To ur of Hidden Naples – Organized by Insolitaguida\n\nDates:  Thursday a t 16:00 (4:00 PM)\n\nAs part of the physical component in Naples\, partici pants will have the opportunity to take part in a guided walking tour orga nized by Insolitaguida\, dedicated to the discovery of some of the most fa scinating legends and hidden treasures of the city.\n\nThe tour will inclu de a visit to the Fontana di Spinacorona\, one of Naples’ most distincti ve fountains\, and to the Church of San Giovanni Maggiore\, which houses t he memorial stone associated with the legendary siren Parthenope\, the myt hical founder of Naples.\n\nThe itinerary will conclude at the Church of S anta Maria la Nova\, where\, according to a fascinating local tradition\, the tomb of Dracula\, Vlad III of Wallachia\, may be located.\n\nThe cost of the guided tour is €20 per person\, including entrance fees and audio headsets.\n\nTo participate\, students should email info@insolitaguida.it with the subject line: ASMSF2026 – Guided Tour\n\n \n\nFor additional information about the association organizing the event\, please visit the following link: Social Event\nhttps://indico.unina.it/event/116/ LOCATION:University of Naples Federico II (Naples) URL:https://indico.unina.it/event/116/ END:VEVENT BEGIN:VEVENT SUMMARY:L'eredità di Roberto Stroffolini a cento anni dalla nascita DTSTART;VALUE=DATE-TIME:20260925T070000Z DTEND;VALUE=DATE-TIME:20260925T170000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-113@cern.ch DESCRIPTION:Speakers: Bianca Stroffolini (Università di Napoli Federico I I)\, Gianpiero Mangano (Università di Napoli Federico II & INFN)\, Gaetan o Fiore (Università di Napoli Federico II)\, Ofelia Pisanti (Università di Napoli Federico II)\n\n\nRoberto Stroffolini è stato un maestro per mo lti giovani studenti\, insegnando loro come apprendere in autonomia con un a guida sicura. Molti di loro hanno dato il loro contributo allo sviluppo della Fisica Teorica nel Dipartimento di Fisica di Napoli. Questo convegno vuole ricordare e discutere la sua eredità scientifica e didattica.\n\nI nvited speakers:\n\nRomeo Brunetti (Università di Trento)\n\nFranco Bucce lla (già Università di Napoli Federico II)\n\nMaria Ceolin\n\nFrancesco Dell'Isola (Università dell'Aquila)\n\nRodolfo Figari (già Università di Napoli Federico II)\n\nGiuseppe Marmo (Università di Napoli Federico II)\n\nAntonino Sciarrino (già Università di Napoli Federico II)\n\nAles sandro Teta (Università di Roma La Sapienza)\n\n \n\nIl convegno si svol gerà dalle 9:00 alle 18:00 nell'aula 0M04 del Dipartimento di Fisica "E. Pancini"\, Complesso Universitario di Monte S. Angelo.\nhttps://indico.un ina.it/event/113/ LOCATION:Aula Caianiello (Dipartimento di Fisica "Ettore Pancini") URL:https://indico.unina.it/event/113/ END:VEVENT BEGIN:VEVENT SUMMARY:8th International Conference on Duckweed Research and Applications DTSTART;VALUE=DATE-TIME:20260928T120000Z DTEND;VALUE=DATE-TIME:20261002T140000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-117@cern.ch DESCRIPTION:Speakers: Robert Martienssen * (Cold Spring Harbor Laboratory \; Howard Hughes Medical Institute)\, Eric Lam (Department of Plant Biolog y\, Rutgers the State University of New Jersey\, New Brunswick)\, Klaus J. Appenroth (4Department of Plant Physiology\, Matthias-Schleiden-Institute \, Friedrich-Schiller- University of Jena\,)\, Anthony Bishopp (Plant and Crop Sciences\, School of Biosciences\, University of Nottingham)\, Shuqin g Xu (University of Mainz)\, Arturo Marí-Ordóñez (Gregor Mendel Instit ute)\n\n\n\nModel plant and novel crop\, the thousand faces of duckweed\n  \n\nWelcome to the 8th International Conference on Duckweed Research and Applications (ICDRA 2026)\, hosted in Portici (Naples)\, Italy\, from 28 September to 2 October 2026. Building on over a decade of successful meeti ngs\, ICDRA 2026 brings together researchers\, and industry professionals to explore duckweed as both a model plant system and a versatile novel cr op.\n\nThe scientific programme spans five thematic sessions — Genes\, G enomes & Evolution\; Ecology & Diversity\; Cell Biology\, Physiology & Met abolisms\; Microbiome & Interactions\; and Applications — covering the f ull breadth of current duckweed science\, from fundamental genomics to rea l-world applications in food\, feed\, bioremediation\, and bioenergy.\n\nT his edition carries a special significance: 2026 marks the centenary of th e birth of Elias Landolt (1926–2013)\, the Swiss geobotanist whose monog raphic work on the Lemnaceae laid the foundation of modern duckweed taxono my — and in whose honour the genus Landoltia was named. A dedicated comm emorative session will feature a tribute by PD Dr. Klaus-J. Appenroth (Fri edrich Schiller University Jena)\, longtime collaborator and friend of Lan dolt.\n\nThe conference features a distinguished lineup of invited speaker s\, including plenary speaker Prof. Robert A. Martienssen (Cold Spring Har bor Laboratory\, USA) alongside invited talks by Arturo Marí-Ordóñez (G MI\, Austria)\, Shuqing Xu (University of Mainz\, Germany)\, Eric Lam (Rut gers University\, USA)\, Anthony Bishopp (University of Nottingham\, UK)\, Metha Meetam (Mahidol University\, Thailand)\, and K. Sowjanya Sree (Cent ral University of Kerala\, India).\n\nWe look forward to welcoming you to Naples — where science meets history\, culture\, and the best pizza in t he world.\nhttps://indico.unina.it/event/117/ LOCATION:Sala Cinese (Department of Agricultural Sciences of the Universit y of Napoli Federico II\, Portici\, Italy) URL:https://indico.unina.it/event/117/ END:VEVENT BEGIN:VEVENT SUMMARY:Nadia Dominici: From Physics to Neuroscience: Understanding How Hu mans Learn to Move DTSTART;VALUE=DATE-TIME:20261013T140000Z DTEND;VALUE=DATE-TIME:20261013T170000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-119@cern.ch DESCRIPTION:Speaker: Nadia Dominici\nTitle: From Physics to Neuroscience: Understanding How Humans Learn to Move\nhttps://indico.unina.it/event/119 / LOCATION:OMO3 URL:https://indico.unina.it/event/119/ END:VEVENT BEGIN:VEVENT SUMMARY:Colloquia2 DTSTART;VALUE=DATE-TIME:20261103T080000Z DTEND;VALUE=DATE-TIME:20261103T100000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-120@cern.ch DESCRIPTION:https://indico.unina.it/event/120/ LOCATION: URL:https://indico.unina.it/event/120/ END:VEVENT BEGIN:VEVENT SUMMARY:Colloquia3 DTSTART;VALUE=DATE-TIME:20261201T080000Z DTEND;VALUE=DATE-TIME:20261201T100000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-121@cern.ch DESCRIPTION:https://indico.unina.it/event/121/ LOCATION: URL:https://indico.unina.it/event/121/ END:VEVENT BEGIN:VEVENT SUMMARY:14th International Workshop on Ships and Marine Hydrodynamics DTSTART;VALUE=DATE-TIME:20270401T070000Z DTEND;VALUE=DATE-TIME:20270401T170000Z DTSTAMP;VALUE=DATE-TIME:20260907T144300Z UID:indico-event-122@cern.ch DESCRIPTION:https://indico.unina.it/event/122/ LOCATION: URL:https://indico.unina.it/event/122/ END:VEVENT END:VCALENDAR