His current research interests are in the area of fast and efficient and by that “green” digital signal processing and computational intelligence. A special focus lies on speech/audio processing, cognitive systems and energy management, and specially oriented to low-power and real-time applications on embedded platforms. Dr. Squartini is one of the founding members of the research group 3MediaLabs, and has actively participated to various (funded) regional, national and European projects on multimedia Digital Signal Processing. He is founder and CEO of the UnivPM Spin-off DowSee, an engineering company developing ICT solutions for the rational use and saving of energy in smart grids.
He is author and coauthor of many international scientific peer-reviewed articles (more than 150), and member of the Cognitive Computation, Computational Intelligence and Neuroscience, Big Data Analytics and Artificial Intelligence Reviews Editorial Boards (starting from 2011, 2014, 2015 and 2016 respectively). He was also Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems (2010-2016). He is a regular reviewer for several (IEEE, Springer, Elsevier) Journals, Books and Conference Proceedings and in the recent past he organized several Special Sessions at international conferences with peer-reviewing and Special Issues of ISI journals. He joined the Organizing and the Technical Programme Committees of more than 40 International Conferences and Workshops in the recent past. He is the Chair of the IEEE CIS Task Force on Computational Audio Processing and member of the IEEE CIS Task Force on Computational Intelligence in the Energy Domain. He was member of the European Network of Excellence EUCOGIII and he is part of the Executive Board of the SIREN (Italian Society of Neural Networks), and responsible for his University’s participation in the Texas Instruments European University Program. He is also member of the Texas Instrument Expert Advisory Panel.
- Fundamentals of Digital Signal Processing (BSc Level - Electronic Engineering)
- Digital Adaptive Circuits and Learning Systems (MSc Level - Electronic Engineering)
- Electrical Machines and Systems (MSc Level - Mechanical Engineering)