Data Science & Distributed Computing
Essence Research Lab is affiliated with the Knowledge and Data Engineering Systems Group of the Research Section: Information, Data and Analysis (IDA), School of Computing Science. Essence brings together the fundamental research areas of Distributed Data Systems and Data Science at the network Edge.
Essence's strength lies in the spectrum of theoretical backgrounds and applications ranging from distributed data systems, to distributed processing & machine learning at the Edge. Essence focuses on building innovative data and knowledge management systems and applications. Essence undertakes research ubder the School's theme: Understandable Autonomous Systems.
Lab's members collaborate with the Inference, Dynamics and Interaction (IDI) as a source of Machine Learning expertise and the Intelligent Pervasive Systems (iPRISM) as a source of Intelligent Systems expertise.
Essence's Google Maps link
Essence in a Nutshell
- Model re-usability at the Edge; Multi-task Learning at the Edge.[Presentations & Tutorials]
- Resilence in ML Systems; Distributed Decision Making; Optimal Stopping Theory. [Presentations & Tutorials]
- Distributed ML; Federated/Local Learning; combinatorial Multi-Armed Bandits. [Presentations & Tutorials]
Check for Postgraduate Research & PhD Opportunities. Contact: Dr Christos (Chris) Anagnostopoulos