Department of Business Administration invites to a research seminar.
Monday, 28 November 2022 at 12:00-13:00 Zoom
A presentation by Juan Mateos-Garcia, Director of the Data Analytics Practice and George Richardson, Head of Data Science at Nesta in London, United Kingdom.
In this seminar, Nesta will present a vision for data enabled research and innovation policy based on lessons learned in EURITO, a three-year Horizon 2020 project to develop new indicators for research and innovation policy. We argue that new, mission-driven models for R&I policy require indicators and evidence based on new data sources and data science / machine learning methods and provide examples of how that evidence can be deployed across the policy-making cycle. Having done this, we identify supply-side and demand-side barriers to the policy adoption of these new methods, and propose actions to overcome them.
Juan Mateos-Garcia is Director of the Data Analytics Practice at Nesta. He leads a team of data engineers, data scientists, data visualisation developers, policy experts and ethicists using data analytics to advance Nesta’s missions. Juan is interested in how data analytics techniques such as machine learning can be combined with other methods to achieve social impact, in how scientific research and innovation are being transformed by emerging technologies such as Artificial Intelligence, and in the role of policy in ensuring that these emerging technologies evolve in directions consistent with the public interest and conducive towards a fairer society.
George Richardson is the Head of Data Science in the Data Analytics Practice at Nesta in London, United Kingdom. He works alongside a team of data scientists who contribute to Nesta’s missions through research and development, using methods such as machine learning, natural language processing and network science.
This workshop is organised by TalTech Industrial project. TalTech Industrial has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952410.