TEAM

(XXXV cycle) – November 2019 – October 2022)  

Giuseppe's doctoral studies, in the field of Pattern Recognition, have focused on classification systems in unconventional domains with applications to the detection of te Internet traffic typology. 

Next item

(XXXIV cycle) – November 2018 – October 2021) Application of CI techniques in Micro Grids and Electric Vehicles energy management. Development of a Self-Driving System for Electric Boats. Design of an innovative Propulsion System for Electric Boats and development of CI techniques for a Propulsion Control System. These works are part of the joint European project Life for Silver Coast with PoMoS. Development of complete simulation environments in MATLAB. Prototyping of the systems described above with power electronics and monitoring and control electronics based on Arduino.

(XXXIV cycle) – November 2018 – October 2021) whose research activity focuses on the hardware acceleration of machine learning and Big Data Analytics algorithms, through approaches based on distributed computing systems, GPUs, FPGAs.

(XXXII cycle - November 2016 - October 2019) whose research focuses on analysis and modeling algorithms for complex systems through Granular Computing and Evolutionary optimization techniques. Applications to System Biology, Bioinformatics ad clinical diagnostic systems.s.

(XXXII cycle - November 2016 - October 2019) whose research activity focuses on the design and development of multi-agent systems (MASs) for distributed Data Mining and Knowledge Discovery on non-metric spaces.

(XXIX cycle - November 2013 - October 2016) - Title of thesis: "Analysis and modeling of complex networks by computational intelligence techniques". Dr. Maiorino's research focused on the modeling of complex networks, as a way to represent complex natural and artificial systems. In particular, Dr Maiorino's research focused on the study and characterization of protein contact networks (PCN), facing the problem of protein folding, as well as the characterization of binary networks by multifractal analysis of time series extracted from the same networks through stochastic processes. To this aim, he developed Computational Intelligence techniques for complex network synthesis (through evolutionary algorithms) and algorithms for multifractal series detrending by Echo State Networks.

(XXXI cycle - November 2015 – October 2018) – Title of thesis: “Design and Implementation of Machine Learning Techniques for Modeling and Managing Battery Energy Storage Systems”. Ing. Luzi’s research focused on BMS (Battery Management Systems) design, both at the hardware and software level. In particular, innovative algorithms have been developed for accurate estimation of the state of charge, using Computational Intelligence techniques.

(XXVII cycle - November 2011 - October 2014) - Title of thesis: "Granular Computing Approaches for Structured Data Learning and Mining". The research activity of Ing. Possemato has focused in the design and development of data mining systems, classification of sequences and texts, the application of free derivative optimization algorithms to control systems for Smart Grids, simulation and modeling techniques for complex systems. Moreover, she designed an automated email classification system based on the joint use of advanced Granular Computing techniques and evolutionary optimization (genetic algorithms), as part of a research contract with SIAV S.p.A.

(XXVI cycle - November 2010 - October 2013). Thesis title: "Hardware Acceleration of Soft-Computing Algorithms". The research activity of Ing. Cinti focused on the design and development of FPGA-based embedded systems for hardware acceleration of software modules characterized by a high computational cost within data driven modeling systems for pattern recognition (neurofuzzy networks, algorithms for computing dissimilarity measures in graphs and sequences domains).

(XXII cycle - November 2006 - October 2009). Thesis title: "Music Information Retrieval Algorithms". The research activity of Ing. Antonelli focused on the development of robust optimization algorithms for data driven modeling systems and intelligent signal processing. In particular, he developed algorithms for automatic music transcription of audio tracks and for the semantic retrieval of audio information.

(XX cycle - November 2004 - October 2007). Thesis title: "Symbolic Algorithms for Automatic Data Classification of Structured Data". The research work concerned the definition, implementation and development of an innovative technique for classifying structured data, according to the Granular Modeling approach.