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desantis

Ritratto di desantis
Nome Cognome: 
Enrico De Santis
Titolo: 
RTDA
Telefono: 
+39 06644 585 475
Telefono Interno: 
25 475
Stanza: 
110

 

Enrico De Santis (Member, IEEE) received the MASc (Hons.) and the PhD degrees in Information and Communication Engineering from “Sapienza” University of Rome, Italy. During the PhD he worked as an assistant researcher and successively as a postdoc with the Department of Computer Science, Metropolitan University of Toronto. Currently, he holds a researcher position with the Department of Information Engineering, Electronics and Telecommunications (DIET) at “Sapienza”. His research interests conducted in the CIPAR LABS at DIET include artificial intelligence, complex systems and data-driven modeling, natural language processing, computational intelligence, neural networks and fuzzy systems with application to several technical areas such as Smart Grids and predictive maintenance. With regard to the NLP field,  His interests span from the theoretical advances of natural language modeling to applications in text and social data mining. Since 2017, he has joined the innovative startup SisterPomos at “Sapienza” University, managing Artificial Intelligence projects in production environments.

In 2021 he wrote a book published with the ARACNE publishing house entitled "Umanità, Complessità, Intelligenza Artificiale. Un connubio perfetto". The essay has an interdisciplinary perspective and intertwines various topics relating to the relationship between intelligent systems at the basis of Artificial Intelligence and complex systems in a human-centric and systemic perspective.

 

Social links

 

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Last pubblication since 2020

Multifractal Characterization of Texts for Pattern Recognition: on the Complexity of Morphological Structures in Modern and Ancient Languages

E De Santis, G De Santis, A Rizzi

IEEE Transactions on Pattern Analysis and Machine Intelligence

 
2023

 

On component-wise dissimilarity measures and metric properties in pattern recognition

E De Santis, A Martino, A Rizzi

PeerJ Computer Science 8, e1106

2
2022

 

Estimation of fault probability in medium voltage feeders through calibration techniques in classification models

E De Santis, F Arnò, A Rizzi

Soft Computing 26 (15), 7175-7193

1
2022

 

Multifractal Characterization and Modeling of Blood Pressure Signals

E De Santis, P Naraei, A Martino, A Sadeghian, A Rizzi

Algorithms 15 (8), 259-275

 
2022

 

A statistical framework for labeling unlabelled data: a case study on anomaly detection in pressurization systems for high-speed railway trains

E De Santis, F Arnò, A Martino, A Rizzi

2022 International Joint Conference on Neural Networks (IJCNN), 1-8

1
2022

 

A Comparison between Crisp and Fuzzy Logic in an Autonomous Driving System for Boats

E Ferrandino, A Capillo, E De Santis, FMF Mascioli, A Rizzi

2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8

 
2022

 

Progetto “Life for Silver Coast”: sistema di guida autonoma per un battello elettrico

FM FRATTALE MASCIOLI, E Ferrandino, A Capillo, E DE SANTIS, A Rizzi

Memorie-XXXVI Riunione Nazionale dei Ricercatori di Elettrotecnica, 1

 
2022

 

Tecniche di granular computing multi-etichetta in spazi non-metrici per l’analisi della sicurezza delle comunicazioni

R Antonello, G Giuseppe, A Martino, E De Santis, FMF Mascioli

Memorie-XXXVI Riunione Nazionale dei Ricercatori di Elettrotecnica, 1-2

 
2022

 

Ottimizzazione di sistemi lightweight Granular Computing per la classificazione di grafi etichettati

R Antonello, A Martino, B Luca, E De Santis, FMF Mascioli

Memorie-XXXVI Riunione Nazionale dei Ricercatori di Elettrotecnica

 
2022

 

Umanità, complessità e intelligenza artificiale. Un connubio perfetto

E De Santis

ISBN: 9791259945624 9, 1-744

 
2021

 

A Modular Autonomous Driving System for Electric Boats based on Fuzzy Controllers and Q-Learning.

E Ferrandino, A Capillo, E De Santis, FMF Mascioli, A Rizzi

IJCCI, 185-195

1
2021

 

Modelling and recognition of protein contact networks by multiple kernel learning and dissimilarity representations

A Martino, E De Santis, A Giuliani, A Rizzi

Entropy 22 (7), 794

9
2020

 

Facing big data by an agent-based multimodal evolutionary approach to classification

M Giampieri, L Baldini, E De Santis, A Rizzi

2020 International Joint Conference on Neural Networks (IJCNN), 1-8

2
2020

 

An ecology-based index for text embedding and classification

A Martino, E De Santis, A Rizzi

2020 International Joint Conference on Neural Networks (IJCNN), 1-8

3
2020

 

An infoveillance system for detecting and tracking relevant topics from Italian tweets during the COVID-19 event

E De Santis, A Martino, A Rizzi

Ieee Access 8, 132527-132538

45
2020

 

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