Talks

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 “Deep Learning: Theory, Algorithms, and Applications” (workshop su invito), Trento, 21-23 June 2023
  • A toolkit for distributed human-centric AI applications over CPSoS, invited talk, Workshop on Adaptive CPSoS (Hipeac 2023), Toulouse, 18 January 2023
  • Continual learning: a sustainable and scalable way to deep learning, keynote speech, ICDM IncrLearn Workshop 2022, 29 November 2022
  • Reservoir Computing for Distributed and Embedded Systems, invited lecture, SSIE 2022, Brixen, July 11-15, 2022
  • Fundamentals of Reservoir Computing, invited lecture, SSIE 2022, Brixen, July 11-15, 2022
  • A Safe AI-as-a-Service Toolkit, invited talk, 10th International Workshop on Mixed Critical Systems (Hipeac 2022), Budapest, 21 June 2022
  • Deep learning for graphs, invited lecture, Scuola Normale Superiore (SNS), Pisa, 10 May 2022
  • Opportunities & Challenges of Artificial Intelligence, keynote speech, IPG Spring Conference 2022, Firenze, 13 May 2022
  • Deep graph networks, invited lecture, 4th Advanced Course on Data Science & Machine Learning (ACDL 2021), 20 July 2021
  • A Gentle Introduction to Deep Learning for Graphs, invited lecture, IM Science Tech Talks, PUC Minas, 21 May 2021
  • Deep neural networks, invited lectures, Scuola Superiore Università di Udine, 11-12 May 2021
  • Learning for structured data, invited tutorial, 3rd Advanced Course on Data Science & Machine Learning (ACDL 2020), 16-17 July 2020
  • Deep learning for graphs, invited lecture, CALDAM pre-conference Ph.D. school, IIT Kharagpur, 11-12 February 2019
  • Learning Generative Models for Structured Data, research colloquium, CITEC, Bielefeld University, 01 August 2018
  • Deep Learning: Research Directions and Upcoming Challenges, Keynote Speech at CHPC 2017, Pretoria, 5 December 2017
  • Deep Learning: Trends and Challenges, Keynote at Dell EMC Accelerating Understanding Summit 2017, Pisa, 26 September 2017
  • Combining IoT and Intelligent Robotics: Challenges and Opportunities, Invited Panel at IoT Forum, Geneva, 7 June 2017
  • Learning Bayesian Network skeletons with high-dimensional and large-sample size data, Invited Lecture at Kings College, London, 21 February 2012
  • Bayesian network structure learning for high-dimensions and large samples, Invited Lecture at Computing for Graphical models, Royal Statistical Society, London, 16 December 2011
  • Unsupervised and Semi-Supervised Image Clustering by Multi-resolution Probabilistic Learning,  Istituto di Scienza e Tecnologie dell’Informazione, CNR, Pisa, 16 February 2010
  • Understanding Visual Content: A Multi-resolution Neuro-Probabilistic Approach, Invited Seminar, IMT Lucca Job Market, 3rd June 2009
  • A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections, E. R. Caianiello Invited Lecture at WIRN’09, Vietri sul Mare (SA), 29 May 2009
  • A Multilayered Latent Aspect Model for Multimodal Image Collections, Invited Seminar, HCI Colloquium, University of Heidelberg, 19 March 2009
  • Probabilistic Generative Models for Machine Vision, Invited Seminar, Università di Padova, 05 March 2009
  • A Perceptual Learning Model to Discover the Hierarchical Latent Structure of Image Collections,  Invited Seminar, Liverpool John Moores University, November 2008

Talks at International Conferences and Workshops

  • Randomly Coupled Oscillators, ECML/PKDD 2023 Workshop on Deep Learning meets Neuromorphic Hardware, 18 September 2023
  • Deep Learning for Graphs, ESANN 2022, October 2022
  • TEACHING – Trustworthy autonomous cyber-physical applications through human-centred intelligence, COINS’21, August 2021
  • Deep learning for graphs, Tutorial, IJCNN’21, July 2021
  • Tensor Decompositions in Deep Learning, ESANN’20, October 2020
  • Deep learning for graphs: Processing symbolic relationships with neural networks, Tutorial, ECAI’20, July 2020
  • Deep learning for graphs, Tutorial, WCCI’20, July 2020
  • A non-negative factorization approach to node pooling in graph convolutional neural networks, AIIA’19, November 2019
  • Deep learning for graphs, Tutorial, IJCNN’19, July 2019
  • Deep learning for graphs, Tutorial, INNS-BDDL’19, April 2019
  • Deep learning for graphs, Tutorial, ECML-PKDD’18, September 2018
  • Concentric ESN: Assessing the Effect of Modularity in Cycle Reservoirs, WCCI’18, July 2018
  • Bioinformatics and medicine in the era of deep learning, ESANN’18, April 2018
  • Hidden Tree Markov Networks: Deep and Wide Learning for Structured Data, SSCI-DL’17, November 2017
  • On the Need of Machine Learning as a Service for the Internet of Things, IML’17, October 2017
  • DropIn: Making Neural Networks Robust to Missing Inputs by Dropout, IJCNN’17, May 2017
  • ELM Preference Learning for Physiological Data,  ESANN’17, April 2017
  • Learning Neural-Generative Models for Structured Data, MLDM’16, November 2016
  • LOL: An Investigation into Cybernetic Humor, or: Can Machines Laugh?, FUN’16, June 2016 (co-starring with Vincenzo Gervasi)
  • A Reservoir Activation Kernel for Trees, ESANN’16, April 2016
  • ESNigma: efficient feature selection for Echo State Networks, ESANN’15, April 2015
  • Modeling Bi-Directional Tree Contexts by Generative Transductions, ICONIP’14, November 2014
  • An Iterative Feature Filter for Sensor Timeseries in Pervasive Computing Applications, EANN’14, September 2014
  • Learning Context-Aware Mobile Robot Navigation in Home Environments, IISA’14, July 2014
  • A General Purpose Distributed Learning Model for Robotic Ecologies, SYROCO’12, September 2012
  • Input-Output Hidden Markov Models for Trees, ESANN’12, 25th April 2012
  • Predicting user movements in heterogeneous indoor environments by reservoir computing, STAMI’11, July 2011
  • Bottom-up Generative Modeling of Tree-Structured Data, ICONIP’10, November 2010
  • Compositional Generative Mapping of Structured Data, IJCNN’10 – WCCI’10, July 2010
  • Are Model-based Clustering and Neural Clustering Consistent? A Case Study from Bioinformatics, KES’08, September 2008
  • Convergence Behavior of Competitive-Repetition Suppression Clustering, ICONIP’07, November 2007
  • A Robust Bio-Inspired Clustering Algorithm for the Automatic Determination of Unknown Cluster Number: IJCNN’07, August 2007
  • Simultaneous Clustering and Feature Ranking by Competitive Repetition Suppression Learning with Application to Gene Data: CIMED’07, July 2007
  • Fuzzy Agreement for Network Service Contracts: CIEF’07, July 2007
  • A fuzzy approach for negotiating quality of services: TCG’06, November 2006
  • Competitive Repetition Suppression Learning: ICANN’06,  September 2006

Research Seminars & Dissemination

  • Arte e coscienza artificiale: la matematica della creatività sintetica, Casa del Mantegna, 01 Decembre 2023
  • Ricerca e pratica dell’IA per migliorare e potenziare la condizione umana, Internet Festival, Centro Congressi Le Benedettine, Pisa, 08 October 2023
  • Singolare, sovraumana o autonoma? Aggettivi per l’intelligenza artificiale di oggi e di domani, UMANia 2022, 6 April 2022
  • AI and bioinformatics: integrating learning and biomedical knowledge, organizer and moderator, theme development workshop on “AI for Future Healthcare”, TAILOR-VISION joint initiative, 16 December 2021
  • Experiences of H2020 project coordination, panelist, APRE Annual Conference, 10 November 2021
  • L’intelligenza artificiale in Italia, lecture, Brasilian embassy in Italy, 15 June 2021
  • L’intelligenza artificiale per l’analisi di dati multimodali, Seminario di Cultura Digitale, 1 April 2020
  • Dati e AI, KRINO student association, panel member, 5 December 2019
  • Learning to deal with networks, relationships and information in context, GATE Academy-Industry talks, 9 December 2019
  • Intelligenza artificiale, lecture for the Pensiero Computazionale programme, 27 November 2019
  • EU and Italian Initiatives in AI and Health, Panel member, ICAIH 2019, Milan, 14 November 2019
  • Ora che comanda lui, quando tutto è basato sul software, Panel member, Informatica50 celebratory event, Pisa, 04 November 2019
  • How can Al help universities and researchers in Europe?, Panel member, Science|Business conference, Bruxelles, 10 September 2019
  • Creatività Artificiale: reti neurali, arte e probabilità, Amico Museo 2019, Museo degli Strumenti per il Calcolo, Pisa, 29 Maggio 2019
  • Bioinformatica intelligente – Il deep learning per grafi e le sue applicazioni biomediche e farmaceutiche, BIGDATATECH 2018 “Data for Human”, Milano, October 2018
  • Citizen Brain – La Comunicazione Politica al Tempo del Deep Learning, Internet Festival, Pisa, October 2018
  • Machine Learning tra IoT e Industria 4.0, TOI industrial seminars, 21/06/2018
  • Artificial Intelligence Research at DI.UNIPI, JRC meets UNIPI day, 17/05/2018
  • Intelligenza Artificiale: Illusioni, Rinascite e Prospettive, Open talk at Fondazione Palazzo Blu, Pisa, 21/03/2018
  • Machine Learning per Banking e Finanza, Seminar at Monte Paschi di Siena, Florence, 21 September 2017
  • I Neuroni alla Conquista di Google – Le reti neurali artificiali dal Percettrone al Deep Learning: Internet Festival, Pisa, October 2015
  • Repetita Iuvant? Constructive and destructive effects of redundancy and repetition in art, biology and computer science: CSE Seminars, IMT Lucca, May 2006