Pervasive & Distributed Intelligence
The Pervasive & Distributed Intelligence (Essence) Research Lab is affiliated with the Research Section
Information, Data and Analysis (IDA)
in the School of Computing Science. The lab brings together the fundamental research areas:
(i) Predictive Computing, (ii) Network-centric Information Systems, and (iii) Distributed Intelligence.
The lab's strength lies in the spectrum of theoretical backgrounds and applications ranging from Context-awareness, Stochastic Optimization, Intelligent Systems, Distributed Statistical Learning to Mobile and Wireless Networking. Essence focuses on building innovative context-aware networked data systems and applications. Essence undertake research ubder the School's themes: Autonomous Systems and Data Science.
The Essence lab's members collaborate with the Inference, Dynamics and Interaction (IDI) group as a source of Machine Learning expertise, and with the Networked Systems Research Laboratory (Netlab) group as a source of Networking expertise.
Note: The Essence's logo is a regular dodecahedron, i.e., a polyhedron with twelve flat faces (Platonic solid), whose coordinates derive from the multiplicative inverse of Pythagora's golden ratio.
Research Areas & Outcome
Essence in a Nutshell
- Methods: Machine Learning; Adaptive Control; Concept Drift. [Presentations & Tutorials]
- Methods: Learning Automata; Optimal Stopping Theory. [Presentations & Tutorials]
- Methods: Stochastic Optimization; Distributed Context-Reasoning; Statistical Learning. [Presentations & Tutorials]
- Methods: Federated/Local Learning Models; Optimal Stopping & Control Theory. [Presentations & Tutorials]
- Methods: Particle Swarm Optimization; Statistical Learning. [Presentations & Tutorials]
- Methods: Data Dissemination; Statistical Learning; Information Theory [Presentations & Tutorials]
Check for Postgraduate Research & PhD Opportunities. Contact: Dr Christos Anagnostopoulos