Research

My research interests lie in the fields of computational intelligence and machine learning, primarily in complex structured-data processing (sequences, trees, graphs), deep learning, Bayesian and graphical models, recurrent and recursive neural networks and distributed/embedded learning systems.

My research activity deals primarily with the design of novel machine learning models and the development of impacting applications exploiting advanced machine learning solutions. Relevant applications of my research include Big Data analysis, biomedical data analysis, machine vision, ambient intelligence, Internet of Things and robotics.

I am the coordinator of a 3-years national project on Learning non-Isomorph Structured Trasnductions for Image and Text (LISTIT) funded by a competitive MIUR-SIR grant. I am also (co) principal investigator of industrial research projects in the area of biomedical and big data analysis and I have participated as key researcher to a number of EU funded project on robotics and ambient assisted living.

A (partial) list of my research keywords follows

  •     Recurrent and Recursive Neural networks
  •     Deep learning
  •     Probabilistic graphical models
  •     Structured data processing
  •     Learning structured transductions
  •     Ambient intelligence
  •     Machine learning for Internet of Things and robotics
  •     Machine learning for Big Data
  •     Biomedical data analysis
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