
The DSS center provides space for researchers and practitioners to share insights, explore emerging trends, and discuss the latest innovations in data science, AI, and simulation techniques. These sessions foster collaboration, spark new ideas, and offer opportunities to stay at the forefront of data-driven research and application.

The Centre of Competence for Data Science and Simulation (DSS) is a cross-departmental initiative. Our ambition is to develop infrastructure, tools and competences in ML, Big Data, microsimulation and geoexperimentation to conduct excellent research and advise policy-makers as well as stakeholders.
The main goal of this Centre is to shape research activities (topics, tools and team) to anticipate the broad diffusion of AI in the economy and society through:
Simon Munzert (Hertie School), 6 November 2024
Étienne Bacher (LISER), 25 Sept 2024
Mohammad Ghoniem & Nicolas Médoc (LIST), 24 April 2024
Joscha Krause (Cure Intelligence), 14 February 2024
Jongoh Kim (LISER), 26 Jan 2023
Thiago Brant (LISER), 9 Dec 2022
Nikos Askitas (IZA), 11 March 2025
Christina Langer (Stanford Digital Economy Lab), 11 Dec 2024
Sergio Galletta (Gees Zurich), 24 January 2024
Eduard Storm (RWI-Essen), 25 October 2023
Rana Cömertpay, Narcisse Cha'ngom (LISER), 20 September 2023
Giorgia Menta (LISER), 28 June 2023
Nikos Askitas (IZA Coordinator of Data and Technology), 14 Dec 2022
Felix Stips and Michela Bia (LISER), 10 Nov 2022
Francesco Bongiovanni & Alban Rousset (LuxProvide), 22 May 2024
Carlotta Montorsi (LISER), 1 Feb 2023
Thiago Brant, Étienne Bacher (LISER), 25 May 2023
Étienne Bacher (LISER), 16 March 2023
Terry Gregory and Julio Garbers (LISER), 14 March 2024
Jan Kinne (ZEW and ISTARI), 22 November 2023
Marten During (Luxembourg University), 7 December 2023

Microsimulation uses detailed demographic and economic data to model how policy changes affect individuals or households. By capturing differences in income, age, employment, or family structure, it estimates distributional outcomes and highlights winners and losers. This method supports the design of targeted policies that promote fairness, minimise unintended effects, and improve equity.

SDI is a strategic project to facilitate efficient geographic research data management and sharing within and outside LISER, with complying with well-established Open Data and Research principles including FAIR (Fair, Accessible, Interoperable, Reusable) and TRUST (Transparency, Responsibility, User focus, Sustainability, Technology). The goal is to facilitate the discovery, access, management, distribution, reuse, and preservation of digital geospatial resources while centralising the management of spatial data and information related to multilateral projects for best sharing and exchange between researchers.
The committee includes Christina Gathmann Eugenio Peluso and Olivier Klein.



Feel free to reach out to us via email for any questions, feedback, inquiries, or suggestions.
Short description of DSS flagship projects