Dr Kai Xu is an Associate Professor in Data Analytics at the Middlesex University. He has over 15 year experience in data visualisation and analytics research in both the academic and industry context. He has extensive experience working with the UK government departments and leading defence companies in data analytics projects and received over £12 million in total research funding. His work has won a few international data visualisation awards. More details here: https://kaixu.me/
Dr Kai Xu's research focuses on Visual Analytics, which integrates data visualisation with analytic techniques (such as Machine Learning and Natural Language Processing) to make sense of large and complex data (such as Big Data). By combining the strength of human cognition and computational analysis, this approach allows analysts to gain insight from Big Data faster and deeper than what was previously possible.
Islam, Junayed and Xu, Kai and Wong, B. L. William (2018) Uncertainty of visualizations for SenseMaking in criminal intelligence analysis. In: EuroRV3: EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization (2018), 04-08 June 2018, Brno, Czech Republic.
Islam, Junayed and Wong, B. L. William and Xu, Kai (2018) Analytic provenance as constructs of behavioural markers for externalizing thinking processes in criminal intelligence analysis. In: Community-Oriented Policing and Technological Innovations. Leventakis, Georgios and Haberfeld, M. R. , eds. SpringerBriefs in Criminology . Springer, pp. 95-105. ISBN 9783319892931
Islam, Junayed and Xu, Kai and Wong, B. L. William (2018) Analytic provenance for criminal intelligence analysis. Chinese Journal of Network and Information Security, 4 (2). pp. 18-33. ISSN 2096-109X
Xu, Kai and Zhang, Leishi and Pérez, Daniel and Nguyen, Phong H. and Ogilvie-Smith, Adam (2017) Evaluating interactive visualization of multidimensional data projection with feature transformation. Multimodal Technologies and Interaction, 1 (3). ISSN 2414-4088
Attfield, Simon and Hewitt, Daniel and Xu, Kai and Passmore, Peter J. and Wagstaff, Adrian and Phillips, Graham and Windridge, David and Dash, Greg and Chapman, Richard and Mason, Lee (2016) Addressing VAST 2016 mini challenge 2 with POLAR kermode, classifier, excel on a power wall and data timelines. In: IEEE VAST Challenge 2016, 23 Oct 2016, Baltimore, MD, USA.