Antonio Pietrabissa | Dipartimento di Ingegneria informatica, automatica e gestionale

Professore associato

pagina personale

stanza:

A213

telefono:

+39 0677274040

Biografia

(updated: 31/10/2022)

Antonio Pietrabissa is Associate Professor at the Department of Computer, Control, and Management Engineering “Antonio Ruberti” (DIAG) of the University of Rome Sapienza, where he received his degree in Electronics Engineering and his PhD degree in Systems Engineering in 2000 and 2004, respectively, and where, since 2010, he has been teaching Automatic Control and Process Automation. He holds the National Scientific qualification (ASN) as Full Professor for the disciplinary field of 09/G1 - Systems and control engineering. His main research focus is on the application of control theory to the networks by means of internal model control, Markov decision processes, (deep) reinforcement learning, robust control, non-cooperative control.

Currently, he serves as Associate Editor for Control. Eng. Pract. (Elsevier) and for IEEE Trans. Autom. Sci. Eng.

He is the author of about 60 journal papers and 100 conference papers and book chapters and is co-owner of a patent on applications in the field of computer aids for patients with motor disabilities based on model predictive control. His scientific activity is characterized by the following bibliometric indices:

Scopus: h-index: 20; citations: 1212.
Google Scholar: h-index: 23; quotes: 1695; i-10 index: 55.

Since 2000, he has participated in 18 research projects funded by the European Union (as scientific coordinator of the project 5G-ALLSTARS, on 5G communications, funded within the H2020 Europe-South Korea cooperation, and as scientific coordinator of the research unit of 5 projects), 4 funded by the European Space Agency (ESA) (as scientific coordinator of the project ARIES, on fire emergency prevention), 1 funded by the Italian Space Agency (ASI) (as scientific coordinator of the research unit), 4 National projects (as scientific coordinator of the projects DAAS, on safe communications in explosive risk areas). Currently, he is the scientific responsible of the following research project:

FedMedAI, on medical applications of federated learning (https://sites.google.com/diag.uniroma1.it/fedmedai/home), funded by Regione Lazio (IT).

Interessi di ricerca

Networked Systems
Time-delay systems
Non-cooperative control
Robust control
Markov Decision Processes
Reinforcement Learning
Deep Reinforcement Learning

Membro di

Networked Systems
Cybersecurity

Awards

2021

Best Original Paper Published in the ETRI Journal (2021)

Ultime pubblicazioni

Satellite Integration into 5G: Deep Reinforcement Learning for Network Selection on MACHINE INTELLIGENCE RESEARCH	2022
AdaFed: Performance-based Adaptive Federated Learning on ICAAI 2021: 2021 The 5th International Conference on Advances in Artificial Intelligence (ICAAI)	2021
Bellman's principle of optimality and deep reinforcement learning for time-varying tasks on INTERNATIONAL JOURNAL OF CONTROL	2021
Capacity-constrained Wardrop equilibria and application to multi-connectivity in 5G networks on JOURNAL OF THE FRANKLIN INSTITUTE	2021
Estimation of Granger Causality through Artificial Neural Networks: applications to Physiological Systems and Chaotic Electronic Oscillators on PEERJ. COMPUTER SCIENCE.	2021
Forest fire risk prediction from satellite data with convolutional neural networks on 2021 29th Mediterranean Conference on Control and Automation, MED 2021	2021
Optimal load sharing in reconfigurable battery systems using an improved model predictive control method on 2021 29th Mediterranean Conference on Control and Automation, MED 2021	2021