Keynote Speakers
Radu Prodan
Title: Think Broader, Run Local: Towards Neuro-Symbolic AI at the Edge
Radu Prodan received the PhD degree from the Vienna University of Technology in 2004. He is a professor in distributed systems with the Institute of Information Technology, University of Klagenfurt, Austria. Previously, he was an associate professor with the University of Innsbruck, Austria. His research interests are performance optimization, and resource management tools for parallel and distributed systems. He participated in numerous projects and coordinated the European Union projects ARTICONF and Graph-Massivizer. He has co-authored more than 250 publications and received three IEEE best paper awards.
Abstract:
The presentation starts by reviewing the convergence of two historically disconnected AI branches: symbolic AI of explicit deductive reasoning owning mathematical rigor and interpretability, and connectionist AI of implicit inductive reasoning lacking readability and explainability.
Afterward, it makes a case of neuro-symbolic data processing in knowledge graph representation approached by the Graph-Massivizer Horizon Europe project and applied for anomaly prediction in data centers using graph neural networks. Machine learning-driven graph sampling algorithms support its training and inference on resource-constrained Edge devices. The presentation concludes with an outlook into future projects targeting Edge large language models fine-tuned and contextualized using symbolic knowledge representation for regulatory AI compliance, job market, and medicine.
Sabita Maharjan
Title: Energy Edge Intelligence
Sabita Maharjan [SM’19] is a Full Professor at the Department of Informatics, University of Oslo, Norway from September 2022. She received her Ph.D. degree in Networks and Distributed Systems from the University of Oslo and Simula Research Laboratory, Norway, in 2013. She worked as a Research Engineer in Institute for Infocomm Research (I2R), Singapore in 2010. She was a Visiting Scholar at Zhejiang Univeristy (ZU), Hangzhou, China in 2011, and
a Visiting Research Collaborator in University of Illinois at Urbana Champaign (UIUC), USA in 2012. From 2024-2016 she worked as a Postdoctoral researcher at Simula Research Laboratory (SRL), Norway. From 2017-2022, She worked as a Senior Research Scientist at SRL and SimulaMet, Norway.
Professor Maharjan is a recipient of the IEEE TCGCC Outstanding Young Researcher Award 2020. She is the Highly Cited Researcher for 2021, 2022 and 2023 according to Web of Science- which is an accolade given in recognition of the exceptional research performance demonstrated by multiple highly cited papers that rank in the top 1% of citations for field and year- worldwide. Professor Maharjan’s has served as
– Vice Chair of the IEEE ComSoc Technical Committee on Green Communications and Computing (TCGCC) SIG on Green AI from (2020-2022), as
– Editor for IEEE Transactions on Green Communications and Networking (IEEE TGCN)
– Associate Editor for the IEEE Internet of Things Journal (IoT-J)
– Associate Editor for the IEEE Open Computer Society Journal, and
– Guest Editor for top-tier journals such as IEEE Journal on Selected Areas in Communications (IEEE JSAC), IEEE Trans. on Green Communications and Networking (IEEE TGCN), IEEE Access.
Professor Maharjan was the Technical Program Committee Co-Chair of IEEE SmartGridComm 2024- held in Oslo Norway in Sept. 2024 and the Symposium Chair for the Green Communication Systems and Networks Symposium in the IEEE Globecom 2024- to be held in Capetown, South Africa in December 2024. In the past, she has contributed actively in the technical program committees of conferences including top conferences like IEEE INFOCOM and IEEE IWQoS. Her current research interests include vehicular networks, 5G Beyond and 6G, network security, smart grid, Internet of Things, and artificial intelligence for networks.
Abstract:
As prosumers become active participants and assume the role of important stakeholders in the energy ecosystem, the energy-edge landscape is anticipated to undergo a drastic transformation towards achieving the green transition. Energy Edge Intelligence will play a crucial role in facilitating active participation and contribution from local prosumers as key stakeholders- to enable the massive uptake of renewable power generation from the edge. The efficient use of renewable power generation at the edge and coordinating its massive uptake into the grid for seamless integration of this “new” capacity into the existing energy system- through different interfaces such as aggregators or in the form of microgrids- will essentially require more fine-grained data communication and analytics.
