Data Engineering & 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, Machine Learning, 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 machine learning at the Edge. Essence focuses on building innovative distributed data science and engineering systems.
Essence undertakes research under the School's themes: Understandable Autonomous Systems and Media and Data Science.
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