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I am a Senior Lecturer in Computer Science at Bournemouth University, where I am the Programme Leader for the BSc (hons) in Data Science and Analytics. My technical expertise includes several flavours of artificial intelligence, software engineering and modelling, as well as project management and business development. I am also ITIL and PRINCE2 certified.

After completing a PhD in Artificial Intelligence (AI) and network-based intrusion detection at Bournemouth University in 2010, I joined a start-up in London, working with the UK Government on population-based simulation modelling. I then joined the IT Innovation Centre at the University of Southampton as a Research Engineer, doing applied research in both national and European research and innovation projects. I moved on to a senior position at IT Innovation with technical, management, business development and marketing responsibilities, before I returned Bournemouth University in 2018.

My research is driven by real-world applications, having worked with hundreds of organisations in cross-disciplinary projects over the years...



My most recent research and innovation projects have involved population-level risk stratification to support healthcare policy making, decision support for the safe navigation of shipping voyages across the arctic, and educational gaming to encourage prosocial behaviour in children.

With a background in AI, I have researched and delivered machine learning solutions applied to different real-world problems ranging from network-based intrusion detection to medical diagnosis.

My research has delved into human-machine networks from different perspectives, including risk prediction in online communities, modelling trust, agency and behaviour, population-based simulation focusing on how humans and machines influence each other in increasingly interconnected networks.

In the past, I have researched distributed search and optimisation based on natural computing (computational intelligence). I have applied this to the area of Cloud computing, working on resource optimisation based on predicting application performance.

Journal Articles

  • Tsvetkova, M., Yasseri, T., Meyer, E.T., Pickering, J.B., Engen, V., Walland, P., Lüders, M., Følstad, A. and Bravos, G., 2017. Understanding human-machine networks: A cross-disciplinary survey. ACM Computing Surveys, 50 (1).
  • Kyriazis, D., Engen, V. et al., 2017. CrowdHEALTH: Holistic health records and big data analytics for health policy making and personalized health. Studies in Health Technology and Informatics, 238, 19-23.
  • Engen, V., Vincent, J. and Phalp, K.T., 2010. Exploring Discrepancies in Findings Obtained with the KDD Cup '99 Data Set. Intelligent Data Analysis.
  • Engen, V., Vincent, J. and Phalp, K., 2008. Enhancing network based intrusion detection for imbalanced data. International Journal of Knowledge-Based and Intelligent Engineering Systems, 12 (5-6), 357-367.


  • Marquezan, C.C., Metzger, A., Pohl, K., Engen, V., Boniface, M., Phillips, S.C. and Zlatev, Z., 2017. Adaptive future internet applications: Opportunities and challenges for adaptive web services technology. Application Development and Design: Concepts, Methodologies, Tools, and Applications. 1568-1589.
  • Pickering, J.B., Engen, V. and Walland, P., 2017. The interplay between human and machine agency. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 47-59.


  • Følstad, A., Engen, V., Haugstveit, I.M. and Pickering, J.B., 2018. Automation in human-machine networks: how increasing machine agency affects human agency. 72-81.
  • Jansson, K., Karvonen, I., Kettunen, O., Ollus, M., Hooper, C.J., Engen, V., Pickering, B., Surridge, M. and Redwood, M., 2016. Forecasting impact of technology developed in RandD projects: The FITMAN approach.
  • Eide, A.W., Pickering, J.B., Yasseri, T., Bravos, G., Følstad, A., Engen, V., Tsvetkova, M., Meyer, E.T., Walland, P. and Lüders, M., 2016. Human-machine networks: Towards a typology and profiling framework. 11-22.
  • Engen, V., Brian Pickering, J. and Walland, P., 2016. Machine agency in human-machine networks; impacts and trust implications. 96-106.
  • Phillips, S.C., Bashevoy, M., Boniface, M., Crowle, S., Engen, V., Sinkala, Z. and Wiegand, S., 2015. Linking quality of service and experience in distributed multimedia systems using PROV semantics. 117-126.
  • Kavoussanakis, K., Engen, V. et al., 2013. BonFIRE: The clouds and services testbed. 321-326.
  • Hume, A.C., Engen, V. et al., 2012. BonFIRE: A multi-cloud test facility for internet of services experimentation. 81-96.
  • Engen, V., Papay, J., Phillips, S.C. and Boniface, M., 2012. Predicting application performance for multi-vendor clouds using dwarf benchmarks. 659-665.
  • Phillips, S.C., Engen, V. and Papay, J., 2011. Snow white clouds and the seven Dwarfs. 738-745.
  • Engen, V., Vincent, J., Schierz, A.C. and Phalp, K., 2009. Multi-objective evolution of the pareto optimal set of neural network classifier ensembles. 74-79.
  • Vincent, J., Engen, V., Langenberg, S., Phalp, K., Mintram, R. and Anyakoha, C., 2007. A notation and representation for describing and evolving correlation patterns. 207-212.
The data on this page was last updated at 04:14 on December 15, 2018.