Welcome in the Computational Intelligence and Pattern Recognition cyberspace
Principal Investigator: Prof. F.M.F. Mascioli
Principal Investigator: Prof. Antonello Rizzi
Scientific Coordinator: Enrico De Santis, PhD
Performing research for better understanding complexity around us and for facing the challenges of our times through Artificial Intelligence, Machine Learning, Pattern Recognition and beyond.
Research is what I'm doing when I don't know what I'm doing. ― Wernher von Braun
ARTIFICIAL INTELLIGENCE
EVOLUTIONARY COMPUTATION
GRANULAR COMPUTING
PATTERN RECOGNITION
DEEP LEARNING
NATURAL LANGUAGE PROCESSING
COMPUTATIONAL INTELLIGENCE
SOFT COMPUTING
COMPLEX SYSTEMS MODELLING
This is the Home page of the Computational Intelligence and Pattern Recognition (CIPAR) labs. On this site you will find all the information about our research topics, projects, proposed thesis and our scientific vision, the composition of the team and much more. Happy surfing!
AICS 2024
Artificial Intelligence and Complex Systems - WCCI - IJCNN Special Session
CISEM 2024: Computational Intelligence for Sustainable Energy Management in Microgrids and Renewable Energy Communities - WCCI - IJCNN Special Session
#OPEN DIET 2024
Computational Intelligence
Algorithms and systems aiming to mimic some basic cognitive functions of biological beings, relying on nature imitation.
Soft Computing
Techniques able to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost.
Algorithms rely on nature imitation, with an emphasis on Inductive Reasoning.
Neural Networks
Fuzzy Logic
Evolutionary computation (Genetic Algorithms, Swarm Intelligence)
Pattern Recognition
Theories and methods to design algorithms able to synthesize models that can recognize patterns in noisy data or complex environments, starting from sample data and/or predefined expert knowledge.
Clustering algorithms
Classification systems
Unsupervised modeling systems
Feature extraction and feature selection techniques
Granular Computing
Granular computing (GrC) is an emerging computing paradigm of information processing that concerns the processing of complex information entities called "information granules", which arise in the process of data abstraction and derivation of knowledge from information or data. Generally speaking, information granules are collections of entities that usually originate at the numeric level and are arranged together due to their similarity, functional or physical adjacency, indistinguishability, coherency, or the like. Fort our research GrC is not only an algorithmic paradigm but also a way of multidimensional and systemic thinking for synthesizing intelligent procedures and models in complex systems.
Natural Language Processing
Natural language processing (NLP) is a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.
Research Topics
Machine Learning
Data-driven modeling systems on unconventional domains
Complex Systems modeling and control
Granular Computing
Computational Intelligence applications to engineering problems related to sustainable mobility and green transition:
Micro Grids and Smart Grids Modeling and Control
Li-ion Energy Storage Systems Modeling and Control
Electric and hybrid power train modeling and control
Intelligent Transportation Systems
Data Mining and Knowledge Discovery
Text Classification and Text Mining - Text Generation - Social Network Analysis
Bioinformatics and system biology
Big Data Analytics
Hardware acceleration of machine learning algorithms
Risk analysis and automatic trading systems
Diagnostic systems - Predictive Maintenance
Multi-agents evolutionary learning systems
Profiling and anomaly detection
Machine learning for cybersecurity
Main Courses
Prof. Antonello Rizzi/Ing. Enrico De Santis - Pattern Recognition - Information Engineering Master Degrees, since 2002
Prof. Antonello Rizzi/Ing. Enrico De Santis - Computational Intelligence - Information Engineering Master Degrees, since 2005
Projects
We have several theoretical and applicative research lines grounded on a set of suitable research projects
Thesis
We are able to offer numerous thesis works on various heterogeneous topics and applications
Computational Intelligence and Pervasive Systems Lab (DIET, Roma)
The CIPR Team laboratory is located in the Engineering headquarters of the "Sapienza" University of Rome, a stone's throw from the Colosseum. Specifically, the laboratory is part of the Department of Information Engineering, Electronics and Telecommunications (DIET) located in Via Eudossiana, 18, 00184 Rome RM, next to the precious Basilica of San Pietro in Vincoli.
Intelligent Systems Lab (POMOS, Cisterna di Latina)
An important branch labs of the CIPR Team is located at the Polo Per La Mobilità Sostenibile (POMOS), located in Cisterna di Latina a few kilometers from Rome. The laboratory is easily accessible by train and the station is within walking distance of the Rome-Naples railway line.
This is a selection from our team!
Featured Students' Projects
The Department
The Department of Information Engineering, Electronics and Telecommunications was established on 1st of July 2010 by joining the former Department of Electronic Engineering and the Department of Information Science and Technique (known with its acronym INFOCOM) in the frame of reorganization of Sapienza University. (more)
Address: Piazzale Aldo Moro 5 00185 - Roma , RM , Italy
Our labs is active on the issues of green energy transition and actively collaborates with the research center located in Cisterna di Latina Polo per la Mobilità Sostenibile (POMOS) and with numerous entrepreneurial realities such as the "Sapienza" innovative startup SISTER POMOS, in line with the so-called third mission of the university
“But there’s a big difference between “impossible” and “hard to imagine.” The first is about it; the second is about you!”
― Marvin Minsky
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