The CIML (Computational Intelligence and Machine Learning) group at the department of Computer Science of the University of Pisa has experience in Artificial Intelligence methodologies, ranging from Computational Intelligence to Machine Learning approaches such as Neural Networks, Deep Learning, Probabilistic Learning, Signal and Image processing, and other Pattern Recognition techniques, with an international scientific leadership in topics for Learning in Structured Domains (sequences, trees and graphs/networks). This knowledge led to the development of new methodologies which have been exploited for the design of successful systems in different interdisciplinary application domains.
"Minimum Spanning Set Selection in Graph Kernels" @ GbR 2023 won the best paper award !
Special Issue (2020/2022) on "Deep Neural Networks for Graphs: Theory, Models, Algorithms and Applications" - IEEE Transaction on Neural Networks and Learning Systems: PDF of the call. Read More
Special Issue (2020/2021) on "New Frontiers in Extremely Efficient Reservoir Computing" - IEEE Transaction on Neural Networks and Learning Systems: PDF of the call. Read More
"Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks" @ BIOSTEC 2020 (Bioinformatics 2020) won the best paper award !
Since the 90's the research of the CIML group addresses the development of new Machine Learning methodologies and the analysis of their computational properties. The research is aimed at defining frameworks for the development of intelligent systems and intelligent data analysis tools for learning in structured domains (sequences, trees, graphs) and for the application to innovative interdisciplinary fields.
The design of new learning algorithms includes Neural Networks, Probabilistic models, Reservoir Computing models, Deep Learning approaches, Kernel-based methods, Support Vector Machines, and other Pattern Recognition techniques, with an international scientific leadership in topics for adaptive processing of structured data.
The application fields include Medicine/Health care, BioInformatics, ChemInformatics, Robotics, Intelligent Wireless Sensor Networks, and Signal/Image Processing.
The Group has participated in several EU and national funded projects.
Full Professor, Head of CIML
Full Professor
Associate Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Assistant Professor
Post-Doc Researcher
Post-Doc Researcher
Post-Doc Researcher
Post-Doc Researcher
Post-doc Researcher
Post-Doc Researcher
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
Full Professor
Associate Professor
Associate Professor
Associate Professor
Post-Doc Researcher
Post-doc Researcher
Post-Doc Researcher
Post-Doc Researcher
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
PhD Student
Research Contractor
Researcher
Researcher
PhD Student
A. Micheli
and
D. Tortorella
Discrete-time dynamic graph echo state networks
Neurocomputing,
496,
85-95,
2022
D. Bacciu,
F. Errica,
A. Micheli,
and
M. Podda
A Gentle Introduction to Deep Learning for Graphs
Neural Networks,
129,
203-221,
2020
The CIML group developed and released software and data sets related to the Research Activities, including innovative ML models for structured data code and datasets for the application areas (related to the original paper publications).
See the “Read More” for a complete list.
Current CIML members have been teaching (since early 2000s) courses related to Artificial Intelligence and Machine Learning for the BSc and MSc degrees of the University of Pisa.
A. Micheli, M.Simi
A. Micheli
A. Micheli, C. Gallicchio
A. Micheli
U. Barcaro
A. Micheli
A. Micheli
U. Barcaro
Alessio Micheli
Tel: +39 050 2212798
Email: micheli@di.unipi.it
Dipartimento di Informatica
Largo B. Pontecorvo, 3
56127 Pisa, Italy