Projects 2020-06-30T13:30:23+00:00


FlockAI aims to design innovative AI-enabled self-adaptive algorithms to ease energy consumption and improve data delivery timeliness in drone swarms. To achieve these goals, the project will explore the use of various power-efficient machine learning models for dynamically adjusting, in place, the data sensing and routing of data over drone swarms while maintaining mission requirements. The methods delivered by the project will be placed in a modular and reusable framework for drone swarm operation.


EUNOMIA uses a positive-first approach, where the veracity of content is assessed continuously, via user crowdsourcing, over time. In a verifiable way, the origin and path of each bit of content is checked, and information cascade paths are assessed and visualised to the user. Once trust is attached to paths, the content along them are similarly assigned levels of trustworthiness. Citizen participation is actively encouraged in content verification by voting on content trustworthiness. The aim is that the users will take ownership of the problem of disinformation, not to rely on third party fact-checkers or computer software to do it for them. Eunomia offers the means to any social media user to find out who first generated a piece of information; if and how it changed from origin to destination; and how others perceive it.



didaxtoDidaxTo implements an unsupervised approach for discovering patterns, that will extract a domain-specific dictionary from product reviews. The approach utilizes opinion modifiers, sentiment consistency theories, polarity assignment graphs and pattern similarity metrics. Apart from extracting the dictionary of opinion words, the application allows the evaluation of the dictionary by means of a sentiment classification task on product reviews.

The DidaxTo approach is fully presented in the following paper publiced by the  Knowledge and Information Systems Journal (KAIS).


Pantelis AgathangelouIoannis Katakis, Ioannis Koutoulakis, Fotios Kokkoras and Dimitrios Gunopulos. “Learning Patterns for Discovering Domain Oriented Opinion Words“, Knowledge and Information Systems Journal (Springer), 55(1), pp.45-77, 2018. DOI: 10.1007/s10115-017-1072-y

DidaxTo (the application) is available for free for non-commercial use. It was developed by Pantelis Agathangelou under the scientific supervision of Ioannis Katakis.



CSRC (Cyprus Science and Research Center) will create a Science and Research Centre for promoting innovative research of excellence in Science, Technology, Engineering, Arts and Mathematics (STEAM) Education and in Science Communication. It will aim to enhance everybody’s awareness of scientific and technological endeavours by becoming a unique landmark to be visited by students, educators, entrepreneurs, start-up founders, the wider public and tourists.


The Cyprus Center for Algorithmic Transparency (CyCAT) is an interdisciplinary effort the detection of biases in algorithmic systems as well as the development of more fair and transparent algorithmic processes. We also work with educators and end users in order to promote better awareness of how their interactions feed back into algorithms’ performance/behavior. CyCAT is coordinated by the Open University of Cyprus. The AI Lab at the University of Nicosia is very proud to be a collaborator to this very crucial research task.