Michele Rossi

I am full Professor with the Department of Information Engineering (DEI), University of Padova, Italy and member of the SIGNET research group @DEI. My research focuses on telecommunications systems, learning systems and human data sensing and analysis. For my current research on green mobile networks, see the SCAVENGE You Tube Channel and the GREENEDGE ITN project.


  • 2024-2026: Horizon Europe ROBUST-6G (HORIZON-JU-SNS-2023-STREAM-B-01-04) - ROBUST-6G: Smart, Automated and Reliable Security Service Platform for 6G.
  • 2022-2025: H2020-MSCA-ITN-2020 - ITN GREENEDGE (coordinator) project on Green Edge computing technology for mobile communications Systems.
  • 2019-2022: H2020-MSCA-ITN-2019 - ITN MINTS project on mm-Wave communications and sensing beyond 5G.
  • 2016-2020: H2020-MSCA-ITN-2015 - ITN SCAVENGE project on energy harvesting mobile networks.
  • 2016-2018: PI of the IoT-SURF project (CPDA151221): "IoT-SURF: a unifying abstraction and reasoning framework for connected and unconnected objects", funded by the University of Padova.
  • 2016-2018: Co-PI of the ECCENTRIC project on distributed signal processing and dissemination in energy harvesting sensor networks, funded by Intel ISRA.
  • 2014-2015: PI of a SAMSUNG Global Research Outreach (GRO) project entitled: "Boosting Efficiency in Biometric Signal Processing for Smart Wearable Devices".
  • 2010-2014: Marie Curie Senior Researcher within SWAP (EU FP7-IAPP project on energy harvesting WSNs).
  • 2010-2013: EU IoT-A (FP7, architectures and protocols for the Internet of Things).
  • 2010-2012: PI of the MOSAICS project (CDPA 094077): "MOnitoring Sensor and Actuator networks through Integrated Compressive Sensing and data gathering", funded by the University of Padova.
  • 2008-2010: EU SENSEI project ("integrating the physical world with the digital world of the network of the future"), WISE-WAI project ("wireless sensor networks for smart cities", funded by Cariparo).
  • 2005-2009: collaboration with the Ubiquitous Networking Research group @ DOCOMO Euro-Labs (in Munich, Germany) in the design of distributed storage and data dissemination schemes for wireless systems (Network Coding and Compressive Sensing).
  • 2002-2007: EU EYES (protocols for energy efficient WSNs, 2002-2005), EU Ambient Networks (IP, phase I and II, heterogeneous and ubiquitous wireless networking, 2002-2007), EU e-SENSE (protocols and architectures for WSNs, 2004-2007).
  • 2000-2004: collaborations with ERICSSON, ESA (European Space Agency) and CNIT ("Consorzio Nazionale Interuniversitario per le Telecomunicazioni").


Current courses

If I could give any advice to anyone musically, it’s that you have to just pick some one thing and stick with it, and don’t let anything get you off track. And you have to give back, if someone wants to know how to play a C chord, show them, don’t keep it all for yourself - Joe Diorio
  • Wireless Networks (Dept. of Inf. Engineering): MS level, 6 ECTS.
    This is an advanced course covering the techniques that are used to send data and perform error and congetion control over wireless networks. The focus is on the mathematical analysis of network protocols, providing the student with the ability of performing a performance analysis of complex systems involving wireless nodes, and accounting for the full transmission chain, involving: physical layer processing, channel access (over the link) and congestion control (across the whole network). Main topics. Wireless channels - statistical models: path loss, shadowing, multi-path fading. Link layer technology: review of retransmission techniques for link error recovery, hybrid ARQ designs. Transport protocols - mathematical models and performance analysis: TCP Reno/SACK, TCP CUBIC, TCP over wireless links. IEEE802.11 a/g/ac/ax (Wi-Fi 6): channel access (MAC) protocol rules, design and mathematical analysis. Mathematical analysis of the IEEE 802.11 contention mechanism. Extensions for Quality of Service support and high throughput. Wireless ad hoc networks: channel access and routing protocols.
  • Machine Learning for Human Data (Dept. of Mathematics): MS level, 6 ECTS.
    This is an advanced course presenting AI tools for the analysis of human data such as speech, motion-related patterns, medical images, biometric patterns, etc. HDA focus will mainly be on the AI/ML methods, looking into their definition (architecture design), training and inference (use at runtime). Main topics: unsupervised learning, vector quantization, clustering, Expectation Maximization (EM), Hidden Markov Models (HMM), Neural Networks (NN): feed forward (FFNN), convolutional (CNN) and recurrent (RNN) designs, autoencoders, residual neural networks, transformer models, learning via backpropagation. Signal types: ECG, speech, inertial signals, video. Applications are: ECG signal transmission/compression, user-identification, automatic speech recognition, user authentication and activity recognition via inertial (movement) data.
  • Network Coding (Dept. of Inf. Engineering): MS level, 6 ECTS.
    Main topics: coding on bipartite graphs, decoding via message passing algorithms, random coding: fountain codes, random codes for Unequal Error Protection, distributed fountain codes. Performance evaluation: simulation- and density evolution-based.