I received my MSc in Computer Science from Wroclaw University of Science and Technology (WrUST), Poland, and an MSc in Software Engineering from the Blekinge Institute of Technology, Sweden, both in 2006. I was awarded my PhD in Computer Science in November 2009 from Wroclaw University of Science and Technology, 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 was also a Head of SMART Technology Research Group and a member of Data Science Initiative. In September 2017 I joined UTS as Associate Professor in Network Science.
Over the last few years I have collaborated with various commercial organizations and research groups. These research efforts resulted in publication of over 80 research papers in journals, books and conference proceedings. I have also been involved in several successful research proposals.
GRANTS AND PROJECTS
1. Data Science and Analytics Training and Engagement Services for Business, (08/2016 – 07/2017, budget £50k, Higher Education Innovation Fund, Co-I).
2. 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.
3. 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 goal of this project, coordinated by the Wroclaw University of Technology, is to create European research centre of Network intelliGence for INnovation Enhancement.
4. 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 is 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.
5. 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 focuses 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 is 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”.
6. GRASP# – Groups, Relationships and Activities of Suspected Persons; Analiza otoczenia spolecznego oraz powi?za? sieciowych osób poszukiwanych i podejrzanych o popelnienie przest?pstwa (10/2009–10/2011, 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.
7. IT SOA – Service-Oriented Architectures; Nowe technologie informacyjne dla elektronicznej gospodarki i spolecze?stwa informacyjnego oparte na paradygmacie SOA (01/2009–12/2012, budget £8.480 Mio., Polish Ministry of Science and Higher Education, researcher)
The project was developed within the Regional Operational Programme Innovative Economy 2008-2013. I was a member of the project team that was responsible for development of the model and methods for decision support system in the service oriented knowledge utility system.
8. 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.
9. 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.
10. 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.
11. Nature-inspired Smart Information Systems – Coordination Action project within EU FP6 (11/2005–01/2008, budget 1 Mio. EUR, European Commission, researcher)
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).
Can supervise: YES
My main areas of research are complex networked systems, and analysis of their dynamics and evolution, as well as predictive, adaptive modelling of networked systems. I also recently started research in a new direction – the application of machine learning 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).
a) Intelligent analysis of large complex networks – 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).
b) 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 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.
c) 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.
d) 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.
e) Evaluation of a user position in a social network – during my PhD I conduct research on assessing a position of individuals in networked systems. The position is calculated based on the users activities and their interactions. The method and appropriate algorithms were developed and number of experiments on real-world networks was carried out. The research on evaluating user position was supported by the individual grant that I obtained from the Polish Ministry of Science and Higher Education (06/2008 – 12/2009).
f) Modelling of complex adaptive software systems – the main challenge of the current software systems is to build the systems that will be able to adapt to the changing external environment. The research conducted within the Advanced Software Engineering task within INFER project was focused on developing architectures for complex adaptive systems. I worked on that task when I was employed at BU.
I have taught different units at Undergraduate and Master levels and I have supervised several Undergraduate and Master Projects.
1. Bournemouth University, United Kingdom (2015-2017)
- Postgraduate Framework
2016/2017 – Advanced Data Management, 20 students, unit leader
- Undergraduate Framework
2015/2016 – Data Management, laboratories, 100 students
2015/2016 – Project Management and Teamwork, 180 students, unit leader
2. King’s College London, United Kingdom (2011-2015)
- Postgraduate Framework
2012/2013, 2013/2014 – Project Management, 105 students, module leader
- Undergraduate Framework
2011/2012, 2012/2013 – Data Structures, 180 students, module co-leader
3. Bournemouth University, United Kingdom (2010-2011)
- Postgraduate Framework (Master Course in Information Technology)
2010/2011 – Software Project Management, 13 students, unit leader
2010/2011 – Business System Design, 13 students, unit leader
- Undergraduate Framework
2010/2011 – Data Management, laboratories, 160 students
4. Wroclaw University of Technology, Poland (2006-2009)
- Master Framework (Master Course in Computer Science)
2008/2009 and 2009/2010 – Digital Image Processing, laboratories, lab leader, 45 students
2007/2008 – Data warehouses and data mining, laboratories, lab leader, 30 students
2007/2008 – Interactive web-based multimedia information systems design, laboratories, lab leader, 15 students
2007/2008 – Intelligent information systems, seminars, lab leader, 45 students
- Undergraduate Framework
2009/2010 – Databases, seminars, lab leader, 60 students
2007/2008 and 2008/2009 – Basics of Coding and cryptography, seminars, lab leader, 120 students
© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes.
My activities resulted in maintaining contacts with various research centres including the commercial companies’ research divisions of BT, Research and Engineering Centre, SAS Institute, Badoo, Phorm, and Affectv. The collaboration with Affectv resulted in joint Open Graph Initiative where we organised open challenges based on large social network data sets that come from 50 different social data providers all over the Europe. During my work at KCL I also collaborated and signed a substantial consultancy contract with Badoo, a company which owns a dating-focused social discovery website and has over 170 million active users in 180 countries. Another consultancy contract was signed with Phorm company and its goal was to explore machine learning approaches to analyse company data.
01/2014 – 03/2014 - Consultancy contract with Phorm. The main goal of the contract is 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”. Income: £16,000.
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. Income: £20,000.
Badoo was also involved in my EPSRC First Grant Application and was prepared to financially support the project (£60,000).
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.
My collaboration with Affectv also resulted in their involvement in the application for the Centre for Doctoral Training in Data Science led by Bournemouth University (Prof. Bogdan Gabrys) in 2013.