Kyiv School of Economics visited Johan Skytte Institute within the BRIDGE Project

At the end of May, a delegation from the Kyiv School of Economics (KSE) visited Johan Skytte Institute of Political Studies within the BRIDGE Project. We held an exciting in-person training for KSE colleagues in methods and applications for big data and AI for governance. The aim was to increase research and innovation capacity of Kyiv School of Economics to enhance public participation and evidence-based policymaking in Ukraine.

The first day was led by Anastasija Nikiforova with the focus on public data ecosystems, including responsible AI adoption and best practices of effective data usage. The second and third days instructed by Martin Mölder focused on survey data and analysis of numerical data in R programming environment, covering factor analysis and regression modelling, as well as analysis of textual data in R, embracing sentiment analysis and topic modelling. The fourth day guided by Andres Võrk concluded the training with an overview of Estonian registry data, methods of ex post evaluation, microsimulation models in ex ante policy evaluation, and some machine learning models.

The training was followed by a consortium meeting, where in addition to KSE we were joined by Erasmus University Rotterdam, Technische Universität Berlin and Центр Розвитку Інновацій - Center for Innovations Development. Partners discussed progress on BRIDGE research, teaching, and capacity-related activities for KSE faculty, keen participation of Ukrainian communities in deliberation activities, and plans for the future.

We will continute to collaborate with our learners from Kyiv School of Economics Andrii Darkovich, Valentyn Hatsko, Tetiana Lukeria, Oleh Omelchenko, Ангеліна Шинкаренко, and Michael Vidyakin! Many thanks to the lecturers for fantastic presentations, Anastasia Tereshchuk for practical arrangements on the KSE side, Viktoriia Biliaieva and Riin Teugijas on UT side, and Esther Locher from UTUC for on-site assistance with the training.