Dr. Rob Mastrodomenico obtained a BSc in Mathematics and Statistics and PhD in Statistics at the University of Reading. He has spent his career working as a data scientist in the sports sector, building predictive models for sporting events. In 2011 he set up Global Sports Statistics which provides consultancy and modelling services to clients in the sports sector. Aside from statistics, Rob’s other interest is in programing. He has years of experience in many different languages but has become an advocate for Python and all that it can do to support all aspects of dealing with and modelling data.

Dr. Claudia von Vacano is the Executive Director of the D-Lab and the Digital Humanities at University of California, Berkeley, and is on the board of the Social Science Matrix. She received a Master’s degree from Stanford University in Learning, Design, and Technology. Her doctorate is in Policy, Organizations, Measurement, and Evaluation from UC Berkeley. The Phi Beta Kappa Society, the Andrew W. Mellon Foundation, the Rockefeller Brothers Foundation, and the Thomas J. Watson Foundation, among others, have recognized her scholarly work and service contributions.

Martin Hadley is currently a Research Technology Specialist at the University of Oxford specializing in data visualization. His background is in biophysics and statistical computing, completing his MPhys at University of Leeds. At University of Oxford, Martin is helping to launch a data visualization service for researchers and is experienced in teaching data science skills to social scientists.

Phillip Brooker is an interdisciplinary researcher in the field of social media analytics, with a background in sociology and sociological research methods (incorporating ethnomethodology, conversation analysis, science and technology studies, computer-supported cooperative work, and human-computer interaction). He has previously contributed to the development of Chorus (www.chorusanalytics.co.uk), a data collection and visual analysis package for social science research on Twitter. Phillip also co-convenes the Programming-as-Social-Science (PaSS) network (www.jiscmail.ac.uk/PaSS) which explores computer programming as a subject and methodological tool for social research and teaching. Phillip is currently employed as a Research Associate on CuRAtOR (Challenging Online Fear and Othering), which aims to investigate how online interactions result in 'cultures of fear'.

Richard Traunmüller is currently a visiting Professor of Quantitative Methods at the University of Mannheim and on leave from his Junior Professorship in Empirical Democracy Research at Goethe University Frankfurt. Prior to coming to Frankfurt, he has held positions at the Universities of Konstanz, Berne, Mannheim, and Essex. Richard has taught semester long courses on data visualisation at these universities and has been invited to teach statistical visualisation at the German Institute of Global and Area Studies (GIGA) and the European University Institute (EUI) in Florence. In addition, he is a regular instructor for data visualisation at the Essex Summer School in Social Science Data Analysis. His work has appeared in major social science journals such as Comparative Political Studies, European Journal of Political Research, and Political Analysis, amongst others.

The Royal Statistical Society is a charity which promotes statistics, data, and evidence for the public good; it is one of the world’s leading learned societies and the only UK professional body for all statisticians and data scientists. Its vision is ‘a world where data are at the heart of understanding and decision-making.’

The University of California, Berkeley, Social Science Data Lab (D-Lab) provides researchers access to the cutting edge of the data revolution. Operating as a hub for broad-ranging and multidisciplinary data-intensive social sciences, it advances research excellence by helping the community integrate the latest software, technology, and methods into their research practices.

The Essex Summer School in Social Science Data Analysis at the University of Essex provides a world class education in statistics, data analysis, and research methods. The Summer School consists of three sessions. Each session offers a variety of postgraduate-level courses, which typically run for two weeks. Courses cover quantitative and qualitative research methods, research design, techniques for data collection and measurement, as well as mathematics.