Sarah Birch is Professor of Political Science at King’s College London. She has studied elections and electoral integrity for over 20 years. Her most recent book on this topic is Electoral Malpractice (Oxford University Press, 2011).
Iadh Ounis is a Professor of Information Retrieval at the University of Glasgow. He has been an active researcher in information retrieval since 1994 and has authored over 150 refereed articles and publications. He specialises in large-scale information retrieval, social media mining and retrieval (blog, Twitter, news, etc), and in the efficiency and effectiveness evaluation of search engines. Prof. Ounis is currently the Director of Knowledge Exchange at the Scottish Informatics and Computer Science Alliance (SICSA) and a board member for The Data Lab Innovation Centre.
Dr Craig Macdonald is a Lord Kelvin Adam Smith Research Fellow at the School of Computing Science, University of Glasgow. His research on information retrieval – the science of search engines – encompasses large-scale effective and efficient information retrieval, as well as the sensing of social media through analytics. Recent project has has co-investigated include CROSS (EPSRC), ReDites (EPSRC), SMART (EC FP7) and SUPER (EC FP7). He has over 100 publications in the field of information retrieval, and was a joint coordinator of the Blog (2006-2010) and Microblog (2011-2012) tracks at the Text REtrieval Conference (TREC), run under the auspices of the US National Institutes of Standards & Technology. He tweets over at https://twitter.com/craig_macdonald
Paul Cockshott researches a number of areas including robot vision, parallelism, e-democracy and econophysics. His books include ‘Computation and its Limits’, ‘Classical Econophysics’ and ‘Towards a New Socialism’.
Jeff Fischer is the Senior Electoral Advisor, Communities in Transition at Creative Associates International. He has years of experience in electoral conflict prevention and electoral education, including an MS in Peace Operations Policy from George Mason University. He was previously Executive Vice President and Senior Advisor and Consultant at International Foundation for Electoral Systems from 1990-2006. He has travelled extensively to document and comment on electoral violence in, and provide electoral assistance to, democratizing states.
David Muchlinski’s is a postdoctoral research associate at the University of Glasgow. David received his Ph.D. from Arizona State University. His research focuses on developing machine learning methods to predict instances of large-scale political violence. His research has been published in Political Analysis, Politics and Religion, and by Ashgate Press.
Xiao Yang received his Ph.D. in Computer Science from University of Kent, UK. In 2015, he joined the Information Retrieval Group in University of Glasgow as a postdoctoral researcher for the Electoral Violence project where he works in the fields of social media mining, violent events classification and prediction using machine learning methods. His research interest is mainly in the areas of neural networks, machine learning, data mining/analytics and memristors.