An evening of discussion filmed on Ada Lovelace Day with our awesome panel of leading computational social scientists and data scientists on collaboration, equality, and skills future social scientists need to work with big data.

Collaboration has been a key theme in academia in recent years. Discipline lines have blurred as the research community adopts a more interdisciplinary approach, and the tech industry and social scientists have been trying to work closer together. Meanwhile, the unprecedented growth of large-scale social data has allowed social scientists to investigate research questions at a scale previously unimaginable, fostering the adoption of new skills and partnerships.

But if the collaborative teams and researchers working in these exciting new areas aren’t diverse, how will research findings truly reflect the society we live in?


Collective responsibility is key to change


Hear from our panellists Milena Tsvetkova, Chanuki Seresinhe, Giselle Cory and James Allen Robertson, on how they got started working with data, what exciting projects they’re part of, and what skills they think students should focus on to work with big data, both in industry and academia.



The panel, chaired by Katie Metzler, Associate VP of Product Innovation at SAGE Publishing, will address why gender equality is so important in more male dominated industries and disciplines and why a collective responsibility is key to achieving gender parity.


About the panel



Milena Tsvetkova is an Assistant Professor in the Department of Methodology at the London School of Economics and Political Science. She completed her PhD in Sociology at Cornell University in 2015. Prior to joining LSE in 2017, she was a Postdoctoral Researcher in Computational Social Science at the Oxford Internet Institute, University of Oxford. In her work, Milena uses large-scale online experiments, network analysis, and computational modeling to study fundamental social phenomena such as cooperation, contagion, segregation, and inequality.

Chanuki Illushka Seresinhe a data science researcher at the Alan Turing Institute (the UK national institute for data science and artificial intelligence) and the Lead Data Scientist at Popsa (using AI to automatically curate photo content into beautifully designed physical products). Chanuki's research entails using big online datasets and deep learning to understand how the aesthetics of the environment influences human wellbeing. For example, how might we design our future cities to be conducive to our wellbeing?

Giselle Cory is Executive Director at DataKind UK. Giselle oversees the running of DataKind, empowering the community of volunteers in their use of data for social good. Prior to joining the team at DataKind UK, Giselle worked in Government, think tanks and for national charities. She believes that smart, responsible data collection and use can help the social sector tackle some of the UK's biggest challenges - and change the world!

James Allen-Robertson is a Digital Sociologist interested in utilizing data science techniques for innovative social science research, and in studying the relationship between digital technologies and society. His research emphasizes materiality and design in human technology interaction, with a particular focus on the way in which materiality expresses and influences the dynamics of power.

Katie Metzler is Associate VP of Product Innovation and strategic lead for the SAGE Research Methods product portfolio, which includes Cases, Datasets and Video. She leads the SAGE Ocean initiative which aims to equip every social scientist with the skills and tools they need to do the social science research of the future. As part of this initiative, she led the development of SAGE Campus, a suite of online courses teaching research methods and data science skills to social scientists. She is also responsible for the product management function supporting SAGE’s digital products for the library market, including SAGE Video, Data Planet, SAGE Stats, SAGE Knowledge, CQ Researcher and Business Cases.