RESEARCH

Network and Data Science, Complex Networked Systems, Dynamics of Networks, Predictive Analytics, Adaptation Mechanisms, Motifs, Multirelational Networked Systems My fundamental research focuses on four main topics:

  • Analysis of large-scale complex networked systems
    Analysis of large-scale complex networked systems
  • Analysis of large-scale complex networked systems
    Analysis of large-scale complex networked systems
    the networks that are in the area of my interest are extracted from large datasets obtained from telecommunication companies (British Telecom plc – BT), e-mail servers (WUT, Enron), multimedia sharing systems (Flickr), etc. The first research on investigating and analysing social networks was conducted as part of the EU FP6 Coordination Action project on Nature-inspired Smart Information Systems (11/2005 – 01/2008) where I acted as a member of the Nature-inspired Data Technology focus group. I presented the research results at the NiSIS symposia at Majorca (06/2006), Tenerife (11/2006), and Malta (11/2007).
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  • Dynamics and predictive modelling of complex networked systems
    Dynamics and predictive modelling of complex networked systems
  • Dynamics and predictive modelling of complex networked systems
    Dynamics and predictive modelling of complex networked systems
    this is area that currently becomes the main field of my research efforts. The conducted research is concerned with discovering patterns in nodes’ behaviours and the interactions between them. The analysis of these patterns and their changes in time allows adaptive prediction of the future behaviour of nodes and their relations. One of the ways to model the network dynamics is the application of methods based on the molecular modelling concept and other physically-inspired methods. Another approach that I investigate is the application of machine learning methods to infer and predict the future structure and characteristics of network.
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  • Network motifs method in social networks
    Network motifs method in social networks
  • Network motifs method in social networks
    Network motifs method in social networks
    Network motifs are small subgraphs that reflect local network topology and were shown to be useful for creating profiles that reveal several properties of the network. The outcomes of my research have revealed that motif analysis enables the effective investigation of both network structure and patterns of interactions between nodes within the network. In addition, the analysis of network motifs dynamics can be utilized in detecting and exploration of changes in complex network structures.
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  • Multirelational social networks
    Multirelational social networks
  • Multirelational social networks
    Multirelational social networks
    these are the networks in which more than one type of relationship exists. Different types of relationships can emerge from various communication channels, i.e. based on each communication channel separate relation that can be also called a layer of a network is created. The relationships are extracted from the users activities and if in the system the knowledge about more than one kind of activity is gathered then more than one type of connection can be defined. Different layers can be also built upon various nature of the connections between users, e.g. co-workers, family members, friends. The systems that can be used in such analysis are the multimedia sharing systems such as Flickr or YouTube, which are typical examples of Web 2.0 systems. In my research I have investigated such systems as Flickr, Vimeo, ExtraDom, and recently Badoo.
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I received my MSc in Computer Science from Wroclaw University of Technology (WrUT), Poland, and an MSc in Software Engineering from the Blekinge Institute of Technology, Sweden, both in 2006. I was awarded my PhD in November 2009 from WrUT, and in the same year I was appointed a Senior Visiting Research Fellow at Bournemouth University (BU), where from 2010 I was a Lecturer in Informatics. I joined King’s in November 2011 as a Lecturer in Computer Science. In September 2015 I returned to Bournemouth University as a Principal Academic in Computing where I am also a Head of SMART Technology Research Group and a member of Data Science Initiative.

Complex networked systems, analysis of their dynamics and its evolution, adaptive and predictive modelling of their structure and characteristics as well as the adaptation mechanisms that exist within such systems are in the centre of my research interests. I have recently started research in a new direction – the application of machine learning and predictive modelling approaches to networked, dynamical systems.

Perfect example of such systems is social network, a concept that we all know very well as each of us is a part of one global network. This network is created by people and the interactions between them. We constantly create connections both in the real world (at home, school, office) and in the rapidly growing online world (Facebook, YouTube, Twitter, Flickr). In my research I investigate those systems, their characteristics and how they change over time. Examples of very interesting questions worth investigating are e.g. what causes that when we work together we can achieve more than when we work individually (concepts known as collective intelligence and emerging behaviour) or what makes that some of the videos, pictures, stories spreads through social network so quickly (known as viral chains).

ABOUT

CONSULTANCY AND INDUSTRY COLLABORATION

01/2014 – 03/2014

Consultancy with Phorm. The main goal of the contract was to help company to understand in greater detail the mechanics of company's information system. The title of the project is: “Machine Learning approaches to analyse company data”.

 

01/2013 – 03/2014

Consultancy agreement with Badoo Trading Limited aiming at understanding customer related data. The main goals of the contract were (i) to understand in greater detail the mechanisms of their email-based system, (ii) to develop a meaningful measure of user churn, and (iii) to discover the intentions of users.

 

06/2013 – 01/2016

Collaboration with Affectv company resulted in Open Graph Initiative in which the company opens up its aggregated social data for external world

R&D projects

Data Science and Analytics Training and Engagement Services for Business

 

08/2016 – 07/2017, budget £50k, Higher Education Innovation Fund, Co-I

 

Following the success of recently launched and strongly recruiting MSc in Applied Data Analytics at Bournemouth University, this project will take advantage of large demand and address the widening advanced analytics skills gap. The team will develop and deliver a portfolio of relevant short courses.

 

iCANS initiative – interdisciplinary Complex Adaptive Networks and Systems Theory and Applications

 

05/2012 – 07/2012, budget £2,000, KCL, PI

 

Internal grant at King’s College London, part of EPSRC Bridging the Gaps Interdisciplinary Informatics grant, project leader. The main goal of this initiative was to enhance cross-disciplinary research at KCL by recognising the links between different research groups and individual researchers in the area of complex networked systems as well as organising meetings and discussion panels to develop new ideas for joint research.

 

Grant for grants

 

04/2008–09/2008, budget £15,000, Polish Ministry of Science and Higher Education, Co-I

 

The grant that aimed at providing funds for the proposal preparation of “Advanced Methods in Collaborative Knowledge Acquisition and Processing” project proposal within the EU FP7 People programme.

Grant for Grant in predictive analysis of complex networks – building a Network of Excellence and Programme of Work

 

01/03/2016 – 31/07/2016, budget £2,000, BU, PI

 

Internal grant at Bournemouth University. The main aim wass to build a Network of Excellence (NoE) bringing together people from academia and industry to develop a Programme of Work in the analysis of complex networks. There is no coherent and comprehensive approach to analyse complex networks which is crucial to advance our understanding of changing people’s behaviour. As this is a crossdisciplinary challenge attracting a lot of attention, it cannot be addressed without experts from different fields.

 

The Computational Intelligence Platform for Evolving and Robust Predictive Systems (INFER) project

 

07/2010–06/2014; budget 1.55 Mio. EUR, European Commission, BU Transfer of Knowledge Coordinator

 

Project was funded by the European Commission within the Marie Curie Industry and Academia Partnerships & Pathways (IAPP) programme. Project partners are Evonik Industries from Germany, Research and Engineering Centre (REC) from Poland, and the Smart Technology Research Centre of Bournemouth University in the UK. The project focused on pervasively adaptive software systems for the development of a modular computational INtelligence software platform For Evolving and Robust predictive systems applicable in various commercial settings and industries. The main innovation of the project was a novel type of environment in which the “fittest” predictive model for whatever purpose will emerge either autonomously or by user high-level goal-related assistance and feedback. I acted as the Transfer of Knowledge coordinator at Bournemouth University side and I was also involved in two research tasks: “Advanced software engineering” and “Complexity research”.

 

An individual research grant from the Polish Ministry of Science and Higher Education

 

09/2008–11/2009, budget £8,000, Polish Ministry of Science and Higher Education, PI

 

The title of the grant was “A method for analysis of node position in the network of internet users”, number N516 264935. I was a principal investigator of this project. The goal of the project was to develop a method for estimating position of a node within a social network.

ENGINE: European research centre of Network intelliGence for INnovation Enhancement

 

06/2013 – 05/2017, budget 4.731 Mio. EUR, European Commision, lead at partner organisation

 

The main goal of the project is to enhance the research potential of the ENGINE Centre, an integral part of the Wrocław University of Technology, by know-how exchange, upgrading the laboratories, initializing new perspectives for advanced and innovative research on network intelligence and its deployment in industry, with particliar emphasis on SMEs. The idea of ENGINE – becoming a driving force for cooperation between academic researchers and other various institutions, including industrial and governmental ones and first of all SMEs.

 

GRASP# – Groups, Relationships and Activities of Suspected Persons; Analiza otoczenia spolecznego oraz powiazan sieciowych osób poszukiwanych i podejrzanych o popelnienie przestepstwa

 

0/2009–10/2011, budget £283,000, Polish Ministry of Science and Higher Education, Co-I

 

The research and developmental grant from the Polish Ministry of Science and Higher Education. I was a project co-investigator and a member of the project steering committee. The aim of the project was to investigate and analyse the social connections and characteristics of people accused and suspected of committing crime.

SNAP – Social Network Analysis Platform

 

02/2008–01/2009, budget £2,000, WRUT, PI

 

The grant obtained from the vice-chancellor of the Wroclaw University of Technology. I was the project manager of the “SNAP – Social Network Analysis Platform” project, which was developed by the members of the DaniE group and the purpose of which was to facilitate research on different large social networks. I acted as a member of the Nature-inspired Data Technology (NiDT) focus group within this Network of Excellence. I attended the meetings of the network of excellence at Majorca (06/2006), Tenerife (11/2006), and Malta (11/2007).

 

Nature-inspired Smart Information Systems – Coordination Action project within EU FP6

 

11/2005–01/2008, budget 1 Mio. EUR, European Commission, researcher

 

The grant that aimed at providing funds for the proposal preparation of “Advanced Methods in Collaborative Knowledge Acquisition and Processing” project proposal within the EU FP7 People programme.

 

teaching

contact

Contact

musial.katarzyna@gmail.com;

kmusialgabrys@bournemouth.ac.uk

+44 01202 961109

Research Gate