Wednesday 21 October 2020 at 10:00-11:30 AM (Helsinki, UTC/GMT +03:00, CET +01:00)
The 6G Research Visions Webinar Series: Edge Intelligence highlights the key results of the expert group that prepared the 6G White Paper in Edge Intelligence. In this white paper, we focused on bringing intelligence on the edge of the networks, including edge computing infrastructures and platforms, data and network management, software development for edge, and real-time and distributed training of ML/AI algorithms, along with security, privacy, pricing, and end-user aspects. The webinar highlights especially the application areas for intelligent, AI/ML-capable edge services. The expert group was led by Dr. Ella Peltonen, University of Oulu.
The webinar is moderated by Dr. Marja Matinmikko-Blue from University of Oulu.
Dr Ella Peltonen, University of Oulu, Finland: Vision towards the Intelligent Edge, Dr Atakan Aral, TU Wien, Austria: Distributed training under node and link failures, Dr Adrian Kliks, Poznan University of Technology, Poland: Edge Intelligence -based autonomous driving and platooning: Requirements, challenges and applications. Also, other white paper expert group members will be available for discussion.
After the talks, a minimum of 30 minutes is reserved for discussion on edge intelligence. A recorded video of the webinar will be openly available after the event.
Dr Ella Peltonen is a research scientist with the Center for Ubiquitous Computing, University of Oulu, Finland. She gained her PhD at the University of Helsinki and did her postdoc period at the Insight Centre for Data Analytics, University College Cork, Ireland. She has undertaken research visits to University of California, Berkeley, US, University of Cambridge, UK, University College London, UK, and University of Melbourne, Australia. Her research focuses on pervasive everyday sensing, edge-native machine learning, and “from data to actions” including ubiquitous artificial intelligence and data analytics. Dr Peltonen has been granted the Marc Weiser Best Paper Award in the IEEE PerCom 2015, Rising Stars in Networking and Communications 2017 by N2 Women, The European Initiative EPIC Grant 2018, and Nokia Foundation Jorma Ollila Grant 2018.
Dr. Atakan Aral is a Postdoctoral Research Fellow at the Institute of Information Systems Engineering, Vienna University of Technology (TU Wien). He received a dual MSc degree in Computer Science and Engineering from Politecnico di Milano and Istanbul Technical University (ITU), and a PhD degree in Computer Engineering from ITU in 2016. Dr. Aral received many awards and scholarships from institutions including Italian and Turkish governments for his academic success and is a co-author of the Best Student Paper at CLOSER 2018 as well as a Best Paper Candidate at ICFC 2019. His research interests center around resource management for distributed and virtualized computing architectures, failure resilience techniques for unreliable Edge resources, and distributed/federated machine learning systems that exploit Edge computing.
Adrian Kliks is an associate professor at Poznan University of Technology’s Institute of Radiocommunications, Poland, and he is a cofounder and board member of RIMEDO Labs company. His research interests include new waveforms for wireless systems applying either non-orthogonal or non-contiguous multicarrier schemes, cognitive radio, advanced spectrum management, deployment and resource management in small cells, and network virtualization.
Similarly to the transition from cloud to Cloud Intelligence, we are constantly assisting at an evolution from the “Internet of Things” to the “Internet of Intelligent Things”. There is a need for an “Intelligent Internet of Intelligent Things” to make such internet more reliable, more efficient, more resilient, and more secure. This is exactly the area where 6G communication with edge-driven artificial intelligence can play a fundamental role.
Artificial intelligence on the wireless communication nodes can enable a number of advanced services and quality of service functionalities. We claim that performance, cost, security, efficiency, and reliability are key features and measurable indicators of any Edge Intelligence solutions.
The evolution to the deployment of a new generation of edge intelligence systems, applications and services will take place during the next ten years, with the completion of different technological steps that will provide new devices, technology, and applications.