{"id":15,"date":"2016-03-23T10:05:23","date_gmt":"2016-03-23T09:05:23","guid":{"rendered":"http:\/\/pages.di.unipi.it\/dbacciu\/?page_id=15"},"modified":"2024-01-14T18:32:16","modified_gmt":"2024-01-14T17:32:16","slug":"talks","status":"publish","type":"page","link":"https:\/\/pages.di.unipi.it\/bacciu\/talks\/","title":{"rendered":"Talks"},"content":{"rendered":"<div class=\"publications_detail\">\n<h3><span lang=\"EN-US\">Invited <\/span>Talks<\/h3>\n<ul>\n<li>Pervasive AI: (deep) learning into the wild, keynote speech, 4th International Conference on Deep Learning Theory and Applications (DeLTA 2023), 13 July 2023<\/li>\n<li>Shaping Neural Networks with Dynamical Systems, invited talk, 2023 International Workshop &#8220;Deep Learning: Theory, Algorithms, and Applications&#8221; (workshop su invito), Trento, 21-23 June 2023<\/li>\n<li>A toolkit for distributed human-centric AI applications over CPSoS, invited talk, Workshop on Adaptive CPSoS (Hipeac 2023), Toulouse, 18 January 2023<\/li>\n<li>Continual learning: a sustainable and scalable way to deep learning, keynote speech, ICDM IncrLearn Workshop 2022, 29 November 2022<\/li>\n<li><span id=\"page27R_mcid23\" class=\"markedContent\"><span dir=\"ltr\" role=\"presentation\">Reservoir Computing for Distributed and Embedded <\/span><span dir=\"ltr\" role=\"presentation\">Systems<\/span><\/span>, invited lecture, SSIE 2022, Brixen, July 11-15, 2022<\/li>\n<li>Fundamentals of Reservoir Computing, invited lecture, SSIE 2022, Brixen, July 11-15, 2022<\/li>\n<li>A Safe AI-as-a-Service Toolkit, invited talk, 10th International Workshop on Mixed Critical Systems (Hipeac 2022), Budapest, 21 June 2022<\/li>\n<li>Deep learning for graphs, invited lecture, Scuola Normale Superiore (SNS), Pisa, 10 May 2022<\/li>\n<li>Opportunities &amp; Challenges of Artificial Intelligence, keynote speech, IPG Spring Conference 2022, Firenze, 13 May 2022<\/li>\n<li>Deep graph networks, invited lecture, <a href=\"http:\/\/acdl2021.icas.cc\">4th Advanced Course on Data Science &amp; Machine Learning<\/a> (ACDL 2021), 20 July 2021<\/li>\n<li>A Gentle Introduction to Deep Learning for Graphs, invited lecture, IM Science Tech Talks, PUC Minas, 21 May 2021<\/li>\n<li>Deep neural networks, invited lectures, Scuola Superiore Universit\u00e0 di Udine, 11-12 May 2021<\/li>\n<li>Learning for structured data, invited tutorial, <a href=\"http:\/\/acdl2020.icas.xyz\/\">3rd Advanced Course on Data Science &amp; Machine Learning<\/a> (ACDL 2020), 16-17 July 2020<\/li>\n<li>Deep learning for graphs, invited lecture, <a href=\"http:\/\/cse.iitkgp.ac.in\/conf\/CALDAM\/conferenceschool.php?1548839081\">CALDAM pre-conference Ph.D. school<\/a>, IIT Kharagpur, 11-12 February 2019<\/li>\n<li>Learning Generative Models for Structured Data, research colloquium, CITEC, Bielefeld University, 01 August 2018<\/li>\n<li>Deep Learning: Research Directions and Upcoming Challenges, Keynote Speech at CHPC 2017, Pretoria, 5 December 2017<\/li>\n<li>Deep Learning: Trends and Challenges, Keynote at Dell EMC Accelerating Understanding Summit 2017, Pisa, 26 September 2017<\/li>\n<li>Combining IoT and Intelligent Robotics: Challenges and Opportunities, Invited Panel at IoT Forum, Geneva, 7 June 2017<\/li>\n<li>Learning Bayesian Network skeletons with high-dimensional and large-sample size data, Invited Lecture at Kings College, London, 21 February 2012<\/li>\n<li>Bayesian network structure learning for high-dimensions and large samples, Invited Lecture at Computing for Graphical models, Royal Statistical Society, London, 16 December 2011<\/li>\n<li>Unsupervised and Semi-Supervised Image Clustering by Multi-resolution Probabilistic Learning,\u00a0 Istituto di Scienza e Tecnologie dell&#8217;Informazione, CNR, Pisa, 16 February 2010<\/li>\n<li>Understanding Visual Content: A Multi-resolution Neuro-Probabilistic Approach, Invited Seminar, IMT Lucca Job Market, 3rd June 2009<\/li>\n<li>A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections, <span lang=\"EN-US\">E. R. Caianiello Invited Lecture at <\/span><span lang=\"EN-US\">WIRN&#8217;09<\/span><span lang=\"EN-US\">, Vietri sul Mare (SA), 29 May 2009<\/span><\/li>\n<li>A Multilayered Latent Aspect Model for Multimodal Image Collections, Invited Seminar, HCI Colloquium, University of Heidelberg, 19 March 2009<\/li>\n<li>Probabilistic Generative Models for Machine Vision, Invited Seminar, Universit\u00e0 di Padova, 05 March 2009<\/li>\n<li>A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections,\u00a0<span lang=\"EN-US\"> Invited Seminar, Liverpool John Moores University, November 2008<\/span><\/li>\n<\/ul>\n<\/div>\n<div class=\"publications_detail\">\n<h3><span lang=\"EN-US\">Talks at International Conferences and Workshops<\/span><\/h3>\n<ul>\n<li>Randomly Coupled Oscillators, ECML\/PKDD 2023 Workshop on Deep Learning meets Neuromorphic Hardware, 18 September 2023<\/li>\n<li>Deep Learning for Graphs, ESANN 2022, October 2022<\/li>\n<li>TEACHING &#8211; Trustworthy autonomous cyber-physical applications through human-centred intelligence, COINS&#8217;21, August 2021<\/li>\n<li>Deep learning for graphs, Tutorial, IJCNN&#8217;21, July 2021<\/li>\n<li>Tensor Decompositions in Deep Learning, ESANN&#8217;20, October 2020<\/li>\n<li>Deep learning for graphs: Processing symbolic relationships with neural networks, Tutorial, ECAI&#8217;20, July 2020<\/li>\n<li>Deep learning for graphs, Tutorial, WCCI&#8217;20, July 2020<\/li>\n<li>A non-negative factorization approach to node pooling in graph convolutional neural networks, AIIA&#8217;19, November 2019<\/li>\n<li>Deep learning for graphs, Tutorial, IJCNN&#8217;19, July 2019<\/li>\n<li>Deep learning for graphs, Tutorial, INNS-BDDL&#8217;19, April 2019<\/li>\n<li>Deep learning for graphs, Tutorial, ECML-PKDD&#8217;18, September 2018<\/li>\n<li>Concentric ESN: Assessing the Effect of Modularity in Cycle Reservoirs, WCCI\u201918, July 2018<\/li>\n<li>Bioinformatics and medicine in the era of deep learning, ESANN&#8217;18, April 2018<\/li>\n<li>Hidden Tree Markov Networks: Deep and Wide Learning for Structured Data, SSCI-DL&#8217;17, November 2017<\/li>\n<li>On the Need of Machine Learning as a Service for the Internet of Things, IML&#8217;17, October 2017<\/li>\n<li>DropIn: Making Neural Networks Robust to Missing Inputs by Dropout, IJCNN&#8217;17, May 2017<\/li>\n<li>ELM Preference Learning for Physiological Data,\u00a0 ESANN&#8217;17, April 2017<\/li>\n<li>Learning Neural-Generative Models for Structured Data, MLDM&#8217;16, November 2016<\/li>\n<li>LOL: An Investigation into Cybernetic Humor, or: Can Machines Laugh?, FUN&#8217;16, June 2016 (co-starring with Vincenzo Gervasi)<\/li>\n<li>A Reservoir Activation Kernel for Trees, ESANN&#8217;16, April 2016<\/li>\n<li>ESNigma: efficient feature selection for Echo State Networks, ESANN&#8217;15, April 2015<\/li>\n<li>Modeling Bi-Directional Tree Contexts by Generative Transductions, ICONIP&#8217;14, November 2014<\/li>\n<li>An Iterative Feature Filter for Sensor Timeseries in Pervasive Computing Applications, EANN&#8217;14, September 2014<\/li>\n<li>Learning Context-Aware Mobile Robot Navigation in Home Environments, IISA&#8217;14, July 2014<\/li>\n<li><span lang=\"EN-US\">A General Purpose Distributed Learning Model for Robotic Ecologies, SYROCO&#8217;12, September 2012<\/span><\/li>\n<li><span lang=\"EN-US\">Input-Output Hidden Markov Models for Trees, <\/span>ESANN&#8217;12, <span lang=\"EN-US\">25th <\/span><span lang=\"EN-US\">April 2012<\/span><\/li>\n<li><span lang=\"EN-US\">Predicting user movements in heterogeneous indoor environments by reservoir computing<\/span>, STAMI&#8217;11, July 2011<\/li>\n<li>Bottom-up Generative Modeling of Tree-Structured Data, ICONIP&#8217;10, November 2010<\/li>\n<li><span lang=\"EN-US\">Compositional Generative Mapping of Structured Data, <\/span>IJCNN&#8217;10 &#8211; WCCI&#8217;10<span lang=\"EN-US\">, July 2010<\/span><\/li>\n<li><span lang=\"EN-US\">Are Model-based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics, KES&#8217;08, September 2008<\/span><\/li>\n<li>Convergence Behavior of Competitive-Repetition Suppression Clustering<span lang=\"EN-US\">, ICONIP&#8217;07, November 2007<\/span><\/li>\n<li><span lang=\"EN-US\">A Robust Bio-Inspired Clustering Algorithm for the Automatic Determination of Unknown Cluster Number: IJCNN&#8217;07, August 2007<\/span><\/li>\n<li>Simultaneous Clustering and Feature Ranking by Competitive Repetition Suppression Learning with Application to Gene Data: CIMED&#8217;07, July 2007<\/li>\n<li>Fuzzy Agreement for Network Service Contracts<span lang=\"EN-US\">: CIEF&#8217;07, July 2007<\/span><\/li>\n<li>A fuzzy approach for negotiating quality of services: TCG&#8217;06, November 2006<\/li>\n<li>Competitive Repetition Suppression Learning: ICANN&#8217;06,\u00a0 September 2006<\/li>\n<\/ul>\n<h3><span lang=\"EN-US\">Research Seminars &amp; Dissemination<br \/>\n<\/span><\/h3>\n<ul>\n<li>Arte e coscienza artificiale: la matematica della creativit\u00e0 sintetica, Casa del Mantegna, 01 Decembre 2023<\/li>\n<li>Ricerca e pratica dell\u2019IA per migliorare e potenziare la condizione umana, Internet Festival, Centro Congressi Le Benedettine, Pisa, 08 October 2023<\/li>\n<li>Singolare, sovraumana o autonoma? Aggettivi per l\u2019intelligenza artificiale di oggi e di domani, UMANia 2022, 6 April 2022<\/li>\n<li>AI and bioinformatics: integrating learning and biomedical knowledge, organizer and moderator, <a href=\"https:\/\/www.vision4ai.eu\/ai-for-future-healthcare\/\">theme development workshop on &#8220;AI for Future Healthcare&#8221;<\/a>, TAILOR-VISION joint initiative, 16 December 2021<\/li>\n<li>Experiences of H2020 project coordination, panelist, <a href=\"https:\/\/www.aprecon2021.it\/\">APRE Annual Conference<\/a>, 10 November 2021<\/li>\n<li>L&#8217;intelligenza artificiale in Italia, lecture, Brasilian embassy in Italy, 15 June 2021<\/li>\n<li>L&#8217;intelligenza artificiale per l&#8217;analisi di dati multimodali, Seminario di Cultura Digitale, 1 April 2020<\/li>\n<li>Dati e AI, KRINO student association, panel member, 5 December 2019<\/li>\n<li>Learning to deal with networks, relationships and information in context, GATE Academy-Industry talks, 9 December 2019<\/li>\n<li>Intelligenza artificiale, lecture for the <a href=\"http:\/\/ilpensierocomputazionale.di.unipi.it\/2019\/\">Pensiero Computazionale<\/a> programme, 27 November 2019<\/li>\n<li><a href=\"https:\/\/www.icaih.com\/session\/eu-and-italian-initiatives-in-ai-and-health\/\">EU and Italian Initiatives in AI and Health<\/a>, Panel member, ICAIH 2019, Milan, 14 November 2019<\/li>\n<li><a href=\"https:\/\/www.unipi.it\/index.php\/informatica50-eventi\/event\/4726-ora-che-comanda-lui-quando-tutto-e-basato-sul-software\">Ora che comanda lui, quando tutto \u00e8 basato sul software<\/a>, Panel member, Informatica50 celebratory event, Pisa, 04 November 2019<\/li>\n<li>How can Al help universities and researchers in Europe?, Panel member, <a href=\"https:\/\/sciencebusiness.net\/events\/horizon-europe-new-parliament-new-commission-new-agenda\">Science|Business conference<\/a>, Bruxelles, 10 September 2019<\/li>\n<li>Creativit\u00e0 Artificiale: reti neurali, arte e probabilit\u00e0, Amico Museo 2019, Museo degli Strumenti per il Calcolo, Pisa, 29 Maggio 2019<\/li>\n<li>Bioinformatica intelligente &#8211; Il deep learning per grafi e le sue applicazioni biomediche e farmaceutiche, <a href=\"https:\/\/www.bnova.it\/bigdatatech-2018\/\">BIGDATATECH 2018<\/a> &#8220;Data for Human&#8221;, Milano, October 2018<\/li>\n<li>Citizen Brain &#8211; La Comunicazione Politica al Tempo del Deep Learning, Internet Festival, Pisa, October 2018<\/li>\n<li>Machine Learning tra IoT e Industria 4.0, TOI industrial seminars, 21\/06\/2018<\/li>\n<li>Artificial Intelligence Research at DI.UNIPI, JRC meets UNIPI day, 17\/05\/2018<\/li>\n<li>Intelligenza Artificiale: Illusioni, Rinascite e Prospettive, Open talk at Fondazione Palazzo Blu, Pisa, 21\/03\/2018<\/li>\n<li>Machine Learning per Banking e Finanza, Seminar at Monte Paschi di Siena, Florence, 21 September 2017<\/li>\n<li>I Neuroni alla Conquista di Google &#8211; Le reti neurali artificiali dal Percettrone al Deep Learning: Internet Festival, Pisa, October 2015<\/li>\n<li>Repetita Iuvant? Constructive and destructive effects of redundancy and repetition in art, biology and computer science: CSE Seminars, IMT Lucca, May 2006<\/li>\n<\/ul>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Invited Talks Pervasive AI: (deep) learning into the wild, keynote speech, 4th International Conference on Deep Learning Theory and Applications (DeLTA 2023), 13 July 2023 Shaping Neural Networks with Dynamical Systems, invited talk, 2023 International Workshop &#8220;Deep Learning: Theory, Algorithms, and Applications&#8221; (workshop su invito), Trento, 21-23 June 2023 A toolkit for distributed human-centric AI [&hellip;]<\/p>\n","protected":false},"author":19,"featured_media":0,"parent":0,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-15","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/pages\/15","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/users\/19"}],"replies":[{"embeddable":true,"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/comments?post=15"}],"version-history":[{"count":39,"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/pages\/15\/revisions"}],"predecessor-version":[{"id":1558,"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/pages\/15\/revisions\/1558"}],"wp:attachment":[{"href":"https:\/\/pages.di.unipi.it\/bacciu\/wp-json\/wp\/v2\/media?parent=15"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}