Projects


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Learning and inference methods for dynamic complex networks, National Science Centre (NCN Sonata), 2017 The project will propose methods and algorithms capable of handling the compound nature of modern-era social media networks, as well as their dynamism and complex data structures. These solutions will be used in the learning and inference tasks, as well as the machine learning methods for data spread analysis. Additionally, the aim of the project is to achieve a better understanding of the task of link prediction PM 2017-2020 
Fusion and uncertainty in information diffusion, National Science Centre (NCN Opus), 2017, PM - Prof. Nitesh Chawla Our thesis is that the influence and diffusion in a network depends on various aspects including but not limited to network topology, initial state of nodes, external factors, and their interactions. Proposing appropriate fusion methods of uncertain data and knowledge will enable more accurate modelling of network phenomena. PI 2017-2020 
RENOIR - Reverse EngiNeering of sOcial Information pRocessing, H2020-MSCA-RISE-2015, 2016-19, no. 691152 The general research aim of the Project is to reverse-engineer information dynamics in social networks, such as spreading of innovations and rumors among people, viral spreading of information in social media such as Twitter or Facebook and dynamics of news and their topics across time. Member 2016-2019 
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