Presentations, Seminars and Academic Courses

Seminars | Talks | Courses


  academic seminars   
  1. A robust classifiers for data with ellipsoidal uncertainty seminar at KTU Informatikos fakultetas, Kaunas (LT) – November 27, 2012
  2. Parallel computing: current trends and future directions seminar at KTU Informatikos fakultetas, Kaunas (LT) – November 20, 2012
  3. Decision rules for efficient classification of biomedical data seminar at KTU Informatikos fakultetas, Kaunas (LT) – November 13, 2012
  4. Incremental learning and characterization of biomedical signals seminar at KTU Informatikos fakultetas, Kaunas (LT) – November 8, 2012
  5. Fuzzy supervised classification models seminar at KTU Informatikos fakultetas, Kaunas (LT) – October 30, 2012
  6. Learning on Wireless Sensor Networks: a case study from power grids seminar at KTU Informatikos fakultetas, Kaunas (LT) – October 23, 2012
  7. Spectral based feature selection for a multiclass cell death discrimination problem, seminar at KTU Informatikos fakultetas, Launas (LT) – June 14, 2011
  8. Online Classification of Data Streams for Sensor Networks, seminar at Lietuvos Energetikos Institutas Laboratoty of Systems Control and Automation, Kaunas (LT) - June 17, 2011.
    Classification of Gene Expression Data    . Cost IC0702 Spring School, Asturias (Spain), May 20, 2009.
  9. A Constructive Approach to Incremental Learning. ISI Fundation, Turin, Jan. 15, 2009
  10. Incremental Classification with Generalized Eigenvalues. Polish Academy of Science, Warsaw, Sept. 17, 2007.
  11. A Classification Method based on linear algebra computational kernels, ISTI-CNR, 2005.
  conference and workshop presentations   
  1. Supervised Classification of Biological Data, plenary talk at 5th International Conference on Soft Methods in Probability and Statistics, Oviedo (SP) - September 28, 2010
  2. Mathematical Models of Supervised Learning and their Application to Medical Diagnosis, invited speaker at Center for Mathematical Medicine, Fields Institute Toronto (CA) - June 11, 2010
  3. D. Abbate, M. R. Guarracino, A. Chinchuluun, and P. M. Pardalos. Neural Network Classification with Prior Knowledge for the Analysis of Biological Data, BIOMAT, Campos do Jordao (Brazil), Oct. 2008.
  4. Incremental Generalized Eigenvalue Classification on data stream, invited talk. Workshop on Data Stream Management and Mining. Beijing, Oct. 2008.
  5. G. Attratto, D. Femiano, M. R. Guarracino. Strengthening I-ReGEC classifier. SFC-CLADAG, 2008.
  6. Mathematical Models of Supervised Learning and their Application to Medical Diagnosis. Workshop on Mathematics and Medical Diagnosis, Faculty of Medicine, University of Pisa, Jan. 9, 2007.
  7. A constructive approach to incremental learning, invited talk. Workshop on Data Mining and Mathematical Programming, Centre de Recherches Mathématiques, Montreal (Canada), 2006.
  8. A Parallel Classification Method for Genomic and Proteomic Problems, High Performance Computing in Medicine and Biology, Vienna (Au), 2006.
  9. A Classification Method Based on Generalized Eigenvalue Problems, Optimization in Medicine,Coimbra (PT), 2005.
  10. A new Java software for automatic tumor measurement, Thoracic Imaging and Diagnosis in Chest Disease, Florence, 2005.
  11. HPEC: High Performance Eigenvalue Computation, a software for the evaluation of large sparse eigenvalue problems, Parallel Matrix Algorithms and Applications, Marsiglia (FR), 2004.
  12. Recent advances of MedIGrid, a grid oriented infrastructure for Medical Imaging, SIMAI 2004, Venezia, Sept 2004.
  13. A parallel PSE for Adaptive Optics, Osservatorio d'Arcetri, Supercomputing Workshop, Florence, 2003.
  14. Software architecture of a distributed problem solving environment for scientific applications, EURESCO Conference on Advanced Environments and Tools for High Performance Computing, Albufeira (PT), 2003.
  15. High performance computing in adaptive optics simulation: results and perspectives, INDAM Workshop on GNCS Innovative Projects 2001, Naples, 2002.
  16. High performance computing in adaptive optic simulation with IDL, SIMAI 2002, Cagliari, 2002.
  17. A Grid application for medical imaging, SIMAI 2002, Cagliari, 2002.
  18. Some perspectives on remote visualization on Grid, First Euroglobus Workshop, Marina d'Ugento (LE), 2001.
  academic courses   
  1. Business Information Systems Lab (12 lectures 3 credits) Ms Computer Science degree, U. of Naples Parthenope, 2007/2008.
  2. Business Information Systems Lab (12 lectures 3 credits) Ms Computer Science degree, U. of Naples Parthenope, 2006/2007.
  3. Operating Systems (48 lectures, 12 credits) Computer Science degree, U. of Naples Federico II, 2004/2005.
  4. Operating Systems (48 lectures, 12 credits) Computer Science degree, U. of Naples Federico II, 2003/2004.
  5. Operating Systems (48 lectures, 12 credits) Computer Science degree, U. of Naples Federico II, 2002/2003.
  6. Operating Systems Laboratory (24 lectures) Computer Science degree, U. of Naples Federico II, 2001/2002.
  7. Operating Systems Laboratory (24 lectures) Computer Science degree, U. of Naples Federico II, 2000/2001.
  8. Operating Systems Laboratory (24 lectures) Computer Science degree, U. of Naples Federico II, 1999/2000.
  9. Numerical Analisys (48 lectures) School of Engeenering , U. of Salerno, 1995/1996.
  10. Numerical Analisys Laboratory (24 lectures) School of Engeenering , U. of Naples, 1994/1995.