Marco Miozzo

Ico_CTTC

Sustainable Artificial Intelligence (SAI)

Phd , Researcher

Phone: +34 93 645 29 00

Marco Miozzo received his MSc degree in Telecommunication Engineering from the University of Ferrara (Italy) in 2005 and the PhD from the Technical University of Catalonia (UPC) in 2018. After graduation, he worked from 2006 to 2008 as a Research Engineer in wireless networking for the Consorzio Ferrara Ricerche (CFR) where he collaborated with the Department of Information Engineering (DEI) of the University of Padova, both in Italy.

In 2008, he joined CTTC and since 2019 he coordinates the activities of the research line on ‘Information Engineering for Sustainable Computing’. In CTTC  he has been involved in the development of the LTE module for the network simulator 3 (ns-3) in the framework of the LENA project. He is the maintainer of the PHY and MAC layer of the official distribution. He has been invited as a speaker on several events for presenting his activities on ns-3, among them ETN training schools, ns-3 events and universities masters and doctorate programs.
Currently he is collaborating with the EU H2020 founded MSCA ETN GREENEDGE working on designing a more sustainable paradigm of edge computing and AI solutions and their the integration with energy harvesting techniques in next generation of mobile networks. In detail, he is the Outreach Officer, he is leading WP3 and WP7 activities and he is participating in the coordination of 2 PhD students.  In the past, he has been involved inSCAVENGE, 5G-Crosshaul, Flex5Gwarem, SANSA and SWAP EU funded projects, working on environmental sustainable mobile networks with energy harvesting capabilities through machine learning techniques. He has participated in the preparation of several proposals, both for academic grant and industry contracts, and of CTTC’s strategic plan.

His main research interests are: sustainable mobile networks, green wireless networking, energy harvesting, multi-agent systems, machine learning, green AI, energy ethical consumerism, transparent and explainable AI.

He is within the technical program committee of multiple conferences of IEEE and ACM. He is the author of over 60 papers in scientific journals and international (peer-reviewed) conferences. According to google scholar he has more than 1400 citations and a h-index of 19.  He has been granted with 2 Best Paper Award at IEEE Globecom and IEEE PIMRC conferences. He chaired and co-chaired different sessions in relevant conferences for his field. He participated in the coordination of 2 doctoral thesis and co-directed several master and degree thesis.

Finally, he has been contributing to different technology platforms, like Networld2020, Circular Economy Hotspot Catalunya and standardization bodies (3GPP group). He has been involved in the WALAA project with the WiFi Alliance for evaluating the coexistence between WiFi and LTE technologies in the unlicensed spectrum (LTE-U). This work has been presented as an official contribution in the 3GPP RAN1 meeting of November 2015 (R1-156621).

 

Google Scholar: http://scholar.google.com/citations?user=hO-SrUoAAAAJ&hl=en

ORCID ID: http://orcid.org/0000-0003-3872-5907

 

 

LENA - LENA N-2010-10-11
Urban Traffic Forecasting using Federated and Continual Learning
Proceedings - 2023 6th Conference On Cloud And Internet Of Things, Ciot 2023. pp. 1-8 January 2023.
Lanza C., Angelats E., Miozzo M., Dini P.
10.1109/CIoT57267.2023.10084875 Google Scholar
The Cost of Training Machine Learning Models Over Distributed Data Sources
Ieee Open Journal Of The Communications Society. Vol 4. pp. 1111-1126 January 2023.
Guerra E., Wilhelmi F., Miozzo M., Dini P.
10.1109/OJCOMS.2023.3274394 Google Scholar
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
2023 8th International Conference On Fog And Mobile Edge Computing, Fmec 2023. pp. 93-100 January 2023.
Perifanis V., Pavlidis N., Yilmaz S.F., Wilhelmi F., Guerra E., Miozzo M., Efraimidis P.S., Dini P., Koutsiamanis R.-A.
10.1109/FMEC59375.2023.10306017 Google Scholar
Deep Reinforcement Learning for Autonomous Mobile Networks in Micro-grids
Deep learning for Unmanned Systems. pp. 259-308 October 2021.
Miozzo, Marco, Piovesan, Nicola, Temesgene, Dagnachew, Dini, Paolo
https://doi.org/10.1007/978-3-030-77939-9_8 Google Scholar
Show More
Researcher R3
Researcher PO
Researcher R2
Researcher R2
Researcher R3