Research activities carried out at the Laboratory of Computational Intelligence and Pervasive Systems (CIPS) focus on a wide range of topics pertaining to Computational Intelligence and Machine Learning algorithms (i.e., artificial neural networks, fuzzy logic, evolutionary computation, swarm intelligence, Bayesian inference, and other adaptive and statistical tools) for the solution of both supervised and unsupervised learning problems with application to either theoretical or real-world complex problems, that is time series forecasting, data regression, function approximation, filtering, system modelling and identification, classification, clustering, etc.
The CIPS Lab is supervised by researchers in Electrical Engineering and Computational Intelligence, who manage and coordinate the scientific and experimental activities of research fellows, Ph.D. students, as well as graduate and undergraduate students of Electronics, Telecommunications, Computer Science and Industrial Engineering. Students are also offered the opportunity of joining a network of researchers in other Universities and Research Centers in Italy, Europe, North America and Australasia, and of being involved in R&D projects in collaboration with SMEs and Big Companies working in the field of ICT and other industry applications.
Research topics currently being addressed at the ACTS Lab include:
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Distributed or massively parallel, supervised and unsupervised, learning algorithms for solving real-world problems related to complex systems, sensor networks, multiple data sources, networks of agents, etc.
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Big Data Mining, Large-Scale Machine Learning, Deep Learning;
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Quantum Computing;
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FPGA and GPU acceleration of Pattern Recognition and Computational Intelligence algorithms;
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Low-cost and massively parallel/distributed HW architectures devoted to Computational Intelligence algorithms and distributed learning over networks;
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Analog and mixed-signal circuits for mechatronics and power systems;
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Multimedia signal processing and pervasive computing;
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Granular Computing, Kernel Methods, Feature Generation/Engineering, Dissimilarity Spaces;
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Computational Intelligence for modelling and control of Smart Grids, Energy Storage Systems, Photovoltaic Plants, and Renewable Energy Sources;
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Hardware/software design and development of Battery Management Systems;
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Computational Intelligence for text classification, text retrieval, and text mining on Big Data;
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Any other applications related to Multimedia, Biomedical Systems, Bioinformatics, Telemedicine and e-Health, Econometrics and Stock Market Analysis, Risk Analysis, Safety and Security, Energy and Environment, Cultural Heritage and Arts, e-Learning, Intelligent Transport Systems, Industry 4.0, Smart Cities.
Students and research fellows have access to equipment for experimental activities connected to their research, including:
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Workstations and Xeon-based clusters for software development on Microsoft and Linux platforms;
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Scientific software tools (i.e., Matlab, Maple, Python, R, etc.);
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Embedded systems based on Arduino, Raspberry and Galileo architectures;
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Cyclone IV FPGA boards;
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Intel Xeon Phi co-processors and “Parallella Board” racks;
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Battery Management Systems and basic electronic equipment.
For further information on how to join, please contact the Supervisors at the CIPS Lab: