AI for 6G

AI for 6G Special Session

Venue: 6G Wireless Summit 2020, Levi, Finland
Time: 18-March-2020

Distributed artificial intelligence solutions on the edge of the network is important research topic within the 6G development. The EdgeAI Special Interest Group, which is coordinated together with the 6G and FCAI Flagships, is delighted to present a special session on AI for 6G within the 6G Summit in Levi, Lapland. This special session highlights the current state of the art of edge-driven artificial intelligence research in Finland with invited research talks. As an international guest assistant professor Aaron Ding from TU Delft, Netherlands, shares his view to building EdgeAI solutions towards 6G era. The session ends with a panel of the speakers.

The special session is part of the 6G Summit 2020 program and participation is included in the Summit’s registration. Registration (link). Early bird rate is valid until 31st January.

 

Speakers

Sasu Tarkoma, University of Helsinki: Edge AI: A view from Finland  

Sasu Tarkoma (SMIEEE’12) is a Professor of Computer Science at the University of Helsinki, and Head of the Department of Computer Science. He has authored 4 textbooks and has published over 200 scientific articles.  His research interests are Internet technology, distributed systems, data analytics, and mobile and ubiquitous computing.  He is Fellow of IET and EAI.  He has nine granted US Patents. His research has received several Best Paper awards and mentions, for example at IEEE PerCom, IEEE ICDCS, ACM CCR, and ACM OSR.

 

 

Aaron Ding, TU Delft, Netherlands: Lessons on Building Edge AI Solutions towards 6G 

Aaron Ding is a tenure-track Assistant Professor in the Department of Engineering Systems and Services (ESS) at TU Delft and Adjunct Professor (Dosentti) in Computer Science at University of Helsinki. His research focuses on edge computing, IoT architecture and data-driven networking services. He is currently leading the Cyber-Physical Intelligence (CPI) Lab at ESS with over 12 years of R&D experience across EU, UK and USA. Prior to joining TU Delft, he has worked at TU Munich with Jörg Ott, at Columbia University with Henning Schulzrinne, at University of Cambridge with Jon Crowcroft, and at University of Helsinki with Sasu Tarkoma. He obtained his MSc and PhD both with distinction from University of Helsinki. Part of his PhD programme was carried out at University of Cambridge in UK and at Columbia University (New York) in USA. Aaron is the founder of ACM EdgeSys and Associate Editor for IEEE Open Journal of Intelligent Transportation Systems (OJ-ITS) responsible for areas of mobile edge computing and 5G for smart vehicles. His research has been awarded the Best Paper of ACM EdgeSys, Best-in-Session Presentation Award at IEEE INFOCOM, and ACM SIGCOMM Best of CCR. He is a two-time recipient of the esteemed Nokia Foundation Scholarships.


 

Leena Ruha, University of Oulu: Novel machine learning approach for edge server placement

Leena Ruha (née Pasanen) works as a research scientist at the Research Unit of Mathematical Sciences, University of Oulu. She received her Lic.Phil. degree in statistics in 2006, and her Ph.D. degree in applied mathematics in 2012, both from the University of Oulu. Currently, she participates in a project that is related to the 5th generation mobile network (5G) research. Her research interests include the development and application of statistical and mathematical methods for e.g. distributed systems. She has authored 20 peer-reviewed articles in journals and conferences.


 

Antti Honkela, University of Helsinki and Aalto University: Privacy-preserving machine learning and edge AI  

Antti Honkela is an Associate Professor of Data Science at the University of Helsinki. He is the coordinating professor for the Finnish Center for AI (FCAI) research programme in privacy-preserving and secure AI. He serves as a privacy and anonymity expert in the steering group of Findata, the recently established Finnish Health and Social Data Permit Authority. He has published a number of papers in leading venues in machine learning (ML) and computational biology. He regularly serves as an area chair at leading ML conferences and has organised a number of privacy workshops at leading ML conferences. His research interests include privacy-preserving machine learning, differential privacy and probabilistic inference as well as their applications.


 

Ella Peltonen, University of Oulu (chair) 

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. Her research focuses on pervasive everyday sensing, edge-native machine learning, and “from data to actionsincluding ubiquitous recommendation systems and data analytics. She has been granted Marc Weiser Best Paper Award 2015, Rising Stars in Networking and Communications 2017, The European Initiative EPIC Grant 2018, and Nokia Foundation Jorma Ollila Grant 2018. She is a member of the ACM Future of Computing Academy.

Last updated: 19.2.2020