Manuel Roveri received the Dr. Eng. degree in Computer Science Engineering from the Politecnico di Milano (Italy) in June 2003, the MS in Computer Science from the University of Illinois at Chicago (USA) in December 2003 and the Ph.D. degree in Computer Engineering from the Politecnico di Milano (Italy) in May 2007. He has been Visiting Researcher at Imperial College London (UK) in 2011. Currently, he is an Associate Professor at the Department of Electronics and Information of the Politecnico di Milano (Italy). Current research activity addresses Embedded and Edge Artificial Intelligence, Tiny Machine and Deep Learning, and Learning in nonstationary/evolving environments. Manuel Roveri is a Senior Member of IEEE and served as Chair and Member in several IEEE Committees. He holds 1 patent and has published about 100 papers in international journals and conference proceedings. He is the recipient of the 2018 IEEE Computational Intelligence Magazine "Outstanding Paper Award" and of the 2016 IEEE Computational Intelligence Society "Outstanding Transactions on Neural Networks and Learning Systems Paper Award".
Coursera
Dive into this comprehensive course that covers essential hardware technologies for machine and deep learning. Learn about different families of machine and deep learning platforms, including libraries and frameworks, to enhance your skills in designing and developing smart applications and systems.
Polimi OPEN KNOWLEDGE
Dive into the world of Artificial Intelligence with our comprehensive MOOC on Technologies and Platforms for AI. Learn about the latest hardware technologies tailored for Machine and Deep Learning, from Internet-of-Things units to advanced data center solutions. Explore a wide range of libraries and frameworks that power smart applications and systems development.