Pervasive & Distributed Intelligence
The Pervasive & Distributed Intelligence (Essence) research team is affiliated with the research section Information, Data and Analysis (IDA)
and Networked Systems Research Laboratory (NETLAB)
in the School of Computing Science. The team brings together the fundamental research areas:
(i) Predictive Computing, (ii) Network-centric Information Systems, and (iii) Distributed Intelligence.
The team's strength lies in the spectrum of theoretical backgrounds and applications ranging from Stochastic Optimization, Intelligent Systems, Distributed Statistical Learning to Mobile/Wireless Networking. Essence focuses on building innovative context-aware networked data systems and applications.
The team's expertise is in mobile computing, context-awareness, real-time information processing, and distributed stochastic optimization. Essence vision is to build network-centric data systems and applications reasoning about knowledge.
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 and Prof Dimitrios Pezaros