Paolo Dini | Data Analysis | Best Researcher Award

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Dr. Paolo Dini | Data Analysis | Best Researcher Award

Dr. Paolo Dini | Data Analysis | Leading Researcher at Centre Tecnològic de Telecomunicacions de Catalunya | Spain

Dr. Paolo Dini is a distinguished researcher in the field of information engineering, currently affiliated with the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), where he leads research at the intersection of sustainable computing, wireless communication, and artificial intelligence. Dr. Paolo Dini holds a Ph.D. in Information and Communication Technologies, and his academic foundation has enabled him to make impactful contributions to the development of energy-efficient and intelligent network infrastructures. Over the years, he has amassed a prolific research portfolio with more than 60 peer-reviewed publications and over 2,300 citations, earning him an h-index of 25 and an i10-index of 54, according to Scopus. Professionally, Dr. Paolo Dini has held research and leadership roles in multiple European and international collaborative projects, contributing both to academia and industrial innovation. He has worked alongside prominent researchers from institutions like Ericsson, Politecnico di Bari, University of Padova, and CTTC, fostering multidisciplinary research in areas such as mobile traffic modeling, green networking, and edge intelligence. His expertise includes machine learning for network optimization, distributed systems, multi-agent systems, 5G and beyond architectures, and sustainable AI. These skills are further demonstrated by his role in developing algorithms and models for energy harvesting in mobile networks and predictive analytics for traffic anomaly detection. Dr. Paolo Dini’s research interests continue to evolve with the current technological landscape, focusing on combining AI with wireless systems to enable smarter, greener, and more adaptive communication environments.

Professional Profile: ORCID | Google Scholar

Selected Publications:

  1. Mobile traffic prediction from raw data using LSTM networks (2018) – 245 Citations

  2. HetNets powered by renewable energy sources: Sustainable next-generation cellular networks (2012) – 201 Citations

  3. SolarStat: Modeling photovoltaic sources through stochastic Markov processes (2014) – 108 Citations

  4. Detecting mobile traffic anomalies through physical control channel fingerprinting: A deep semi-supervised approach (2019) – 81 Citations