Machine Learning Methods in Visualisation for Big Data 2018

Tutorial co-located with EuroVis 2018, June 4, 2018, Brno, Czech Republic

Organisation

Organisers:

Ian Nabney is Professor and Head of SCEEM School of Engineering at University of Bristol. He received his BA in Mathematics from Oxford University and a PhD in Mathematics from Cambridge University. He has over 20 years’ experience in machine learning research, has published more than 80 papers (1900 citations), and is the system architect for the Netlab pattern analysis toolbox, which has been downloaded more than 40,000 times since 1999 (the accompanying book has been through three reprints), and the Data Visualisation and Modelling System (DVMS) which integrates data projection and information visualisation techniques to provide a rich interactive environment for data exploration and visual analytics. DVMS will be used for the demonstrations of generative models. He has won grants worth more than 3M GBP from EPSRC, the EU, TSB, and industry and has supervised 11 PhD students to completion. He is the Chair of the Natural Computing Applications Forum, a principal mechanism in the UK for exchange of ideas between academics and industry on natural computing technology and practical applications.

Jaakko Peltonen is a professor of statistics (data analysis) at the Faculty of Natural Sciences, University of Tampere where he leads the Statistical Machine Learning and Exploratory Data Analysis research group; he is also currently visiting professor at the Department of Computer Science, Aalto University. He received his D.Sc. from Helsinki University of Technology in 2004. He is an editorial board member of Neural Networks, associate editor of Neural Processing Letters, editorial board member of Heliyon, and executive committee member of the European Neural Network Society. He has served in organising committees of eight international conferences and in program committees of 44 international conferences/workshops, and has referee duties for numerous international journals and conferences. He is an expert in statistical machine learning methods for exploratory data analysis, visualisation of data, and learning from multiple sources.

Daniel Archambault received his PhD in Computer Science from the University of British Columbia, Canada in 2008. He is currently a Senior Lecturer of Computer Science at Swansea University in the United Kingdom. During his post-doctoral studies at University College Dublin, he applied his expertise in information visualisation to help visualise the results of machine learning approaches, particularly in the area of social media visualisation. This work inspired him to co-chair the AAAI ICWSM Workshop on Social Media Visualisation (SocMedVis 2012 and 2013). His other areas expertise primarily lie in graph visualisation and drawing as well as perceptual factors in information visualisation.