Knowledge & Data Engineering Systems
The Knowledge & Data Engineering Systems (KDES) research group is part of the Information, Data and Analysis (IDA) Section. KDES brings together the fundamental research areas of Distributed Data Systems, Data Engineering, and Data Science.
KDES's strength lies in the spectrum of theoretical backgrounds and applications ranging from large-scale Distributed Computing and Information Systems, to Edge Computing , Distributed Machine Learning/AI, and Data-centric AI, focuses on building innovative distributed data science and engineering systems.
Academic Staff & Members
News & Events
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06 SepOur paper 'Enhancing Knowledge Reusability: A Distributed Multitask Machine Learning Approach' authored by Eric Long, Christos Anagnostopoulos, and Kostas Kolomvatsos has been accepted for publication in IEEE Transactions on Emerging Topics in Computing!
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06 Sep
IEEE ICDCS 2025 in Glasgow!
The 45th IEEE International Conference on Distributed Computing Systems 2025 (IEEE ICDCS) will be held in Glasgow, Scotland, 21-23 July 2025! -
06 Sep
FGCS (Elsevier) Paper!
Our paper 'Autonomous Proactive Data Management in Support of Pervasive Edge Applications' authored by Dr Kolomvatsos and Dr Anagnostopoulos has been accepted in the CORE A Journal: Future Generation Computer Systems (FGCS), Elsevier. -
06 Sep
IEEE ICDM 2023 Paper!
Our paper on ' FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization' has been accepted for presentation at the CORE A* IEEE International Conference on Data Mining (IEEE ICDM 2023 [https://www.cloud-conf.net/icdm2023/]), December 1-4, 2023, Shanghai, China (partially funded by EU Horizon TRACE Grant [https://trace-horizon.eu/]). -
27 Jun
IEEE IE 2023 Paper Presentation
Kian Wang gives a talk on 'Maintenance of Model Resilience in Distributed Edge Learning Environments' at the IEEE Intelligent Environments (IE 2023) Conference, Jun 27, 2023 - Jun 30, 2023, Mauritius.