Invited Talks

  • 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

  • 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

  • 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