AI-SPRINT: An EU Perspective on the Future of AI and Edge Computing

Edge AI is rapidly gaining momentum with growing investments and awareness of its benefits, such as reducing costs and latency times for improved user experience and increased levels of security in terms of data privacy through local processing. 
Yet its full potential has yet to be realised. One way to achieve this is by combining various execution platforms for ubiquitous and seamless execution computing environments for a complete cloud continuum. As a result, application developers will have greater control over computing, network and data infrastructures and services and end-users will benefit from seamless access to continuous service environments. 
This webinar zooms in on how AI-SPRINT is driving innovations in AI and edge computing as a research and innovation action under Europe’s Horizon 2020 programme. Lightning talks from key partners will give examples of new AI applications in edge and cloud environments, top challenges that need addresses and real-world scenarios aimed at proving competitive edge and replicability. 
The panel discussion brings together members of the AI-SPRINT Alliance and project experts for a deep-dive into the challenges, needs and future trends of AI and edge computing from various viewpoints. Participants will also get a chance to learn about the Alliance designed for small SW houses and EU cloud providers to support the AI and edge computing ecosystem while the interactive polls will capture viewpoints from the audience. 

Agenda

About the speakers

Enrico Abate-Daga, Beck et al.

Enrico Abate-Daga is the head of Data to Results Team at Beck et al. He has a Master in Mathematics from the University of Texas. Enrico Abate-Daga has 25 years of professional experience, first as software developer, then as architect and finally as project manager and program manager. In the past five years, he has focused exclusively on Cloud and Big Data projects, in the areas of IT (analysis of logs and monitoring event) and manufacturing (analysis of data from production).

Danilo Ardagna, Politecnico di Milano

Danilo Ardagna is Professor at Politecnico di Milano with a Master degree and PhD in Computer Science from the same university. He was a visiting researcher at IBM TJ Watson Research Center and at the Basque Center for Applied Mathematics. His research interests are performance modelling and cloud/fog systems resource management. He has developed solutions for supporting web services compositions, optimising virtualized systems and advanced schedulers for big data and artificial intelligence applications. 

Atia Cortés, Barcelona Supercomputing Center

Atia Cortés received the M.Sc. and Ph.D. degrees in artificial intelligence from the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, in 2012 and 2018, respectively. She is currently the Co-Director of the Observatory for Society and AI in the AI4EU platform. She is also a Post-Doctoral Fellow with the Barcelona Supercomputing Center, Barcelona. She has been involved in several research projects funded by the Spanish Council and the EU related to AI solutions for health care.

Alfonso Fuggetta, CEFRIEL

Alfonso Fuggetta, CEO and Scientific Director at CEFRIEL, received a Master degree in Electronic Engineering from Politecnico di Milano in 1982. His working experience spans software consulting and research activities at Politecnico di Milano, as well as collaborating with AIPA, CNIPA, the Department of Innovation of the Italian Government, the Ministry of Health, the Ministry of Labour, the Ministry of Education and of the University. He also developed extensive expertise in software engineering, innovation management, application of ICT to conventional processes and industrial sectors, e-government, and public policies.

Matteo Matteucci, Politecnico di Milano

Matteo Matteucci is Associate Professor at Politecnico di Milano. In 1999 he got a M.Sc degree in Computer Engineering at Politecnico di Milano. In 2002 he got a Master of Science in Knowledge Discovery and Data Mining at Carnegie Mellon University and in 2003 he got a PhD in Computer Engineering and Automation at Politecnico di Milano. Since then, his main research topics are pattern recognition, machine learning, machine perception, robotics, computer vision and signal processing. His main research interest is linked to the development, evaluation and application of techniques for adaptation and learning to autonomous systems interacting with the physical world.  

Danilo Pau, STMicroelectronics

One year before graduating from the Polytechnic University of Milan in 1992, Danilo PAU joined STMicroelectronics, where he worked on HDMAC and MPEG2 video memory reduction, video coding, embedded graphics, and computer vision. Today, his work focuses on developing solutions for deep learning tools and applications. 
Since 2019 Danilo is an IEEE Fellow, serves as Industry Ambassador coordinator for IEEE Region 8 South Europe and Member of the Machine Learning, Deep Learning and AI in the CE (MDA) Technical Stream Committee IEEE Consumer Electronics Society (CESoc).
With over 80 patents, 100 publications, 113 MPEG authored documents and 37 invited talks/seminars at various worldwide Universities and Conferences, Danilo's favourite activity remains mentoring undergraduate students, MSc engineers and PhD students from various universities in Italy, US, France and India.  

Domenico Siracusa, Fondazione Bruno Kessler

Domenico Siracusa (PhD) is the head of the RiSING research unit at Fondazione Bruno Kessler. He is project manager and technical leader of the H2020 EU-Korea DECENTER Project. In the past, he coordinated the H2020 ACINO and EIT Digital DigiFlow projects. He authored more than 100 peer-reviewed publications on cloud computing, networking, security and robustness.