The ONS Data Science Campus, the Alan Turing Institute, and the Financial Conduct Authority (FCA) are pleased to present the economic data science seminar series. This series brings together economists and data scientists to showcase work and explore the potential for the development of this fledgling discipline.
The intended audience for these seminars includes both policymakers and academics. The seminars will be overseen by a group of seminar partners made up of representatives of key stakeholder organisations.
Seminars will take place from 4-5pm, with registration open from 3:30pm for each session.
|Date and time||Session title||Speaker||Venue||Register|
|Wednesday 19 February 2020, 4-5pm||Analysis of Networks via the Sparse β-Model||Mingli Chen, University of Warwick||Turing Institute, London||Book now|
|Wednesday 18 March 2020||To be confirmed||Stephen Hansen, Imperial College London||Financial Conduct Authority, London||Available soon|
Further seminars will be taking place on the following dates in 2020. Details of the session, speaker and location will be added here as they become available, but we have provided the dates now so that they can be added to your diary.
|Wednesday 15 April 2020|
|Wednesday 20 May 2020|
|Wednesday 17 June 2020|
|Wednesday 8 July 2020|
Economic data science is a fledgling discipline. Applying the tools and techniques of data science to economic challenges offers rich new opportunities for measuring and understanding the economy.
One important challenge in realising the full benefits of the synthesis of data science and economics is in bringing economists and data scientists together to explore the collaborative opportunities.
The economic data science series has four objectives:
- to promote economic data science as a discipline
- to link researchers across institutions and disciplines and bring together the academic and policy communities
- to demonstrate cutting-edge applications of data science to economic questions to an audience of economists, data scientists and economic data scientists
- to provide a forum for addressing challenges in current work.