Multi-Year Funding Agreement
We happily announce that the CSH will receive a substantial funding from the City of Vienna over the next three years.
Veronica Kaup-Hasler, Science City Councilwoman from the Austrian Socialist Party (SPÖ), said in a statement after the decision: “As a progressive coalition, we think ahead—whether it’s climate protection, digitization or the growing of the city. Here, science offers indispensable, valuable foundations for fact-based decisions and visionary concepts. Most recently, the Corona crisis has made the need for digitalization particularly visible. The insights from data-based digital models provided by complexity research are of great importance for politics and the media, and for society as a whole. The funding of the Complexity Science Hub Vienna is therefore another important step for Vienna as a center of science,” Kaup-Hasler added.
“Vienna has followed science during the pandemic”
Together with Stefan Gara, NEOS Vienna Science Spokesman, Kaup-Hasler came to the Hub this week to meet CSH President Stefan Thurner, our Corona expert Peter Klimek, and our Secretary General Philipp Marxgut. See header picture.
Stefan Gara especially emphasized the importance of the Hub during the Corona crisis. “Vienna has followed science in the COVID-19 pandemic. The CSH is one of these important scientific advisors that support political decisions with their complex simulation models. That is why I am all the more pleased that we as progressive coalition are providing more research funding. In this way, Vienna is also gaining in radiance as a metropolis of science,” Gara said.
Our president Stefan is looking forward to (even more) interesting projects. “At the Hub, we want to use data in a way that is useful for society, without abandoning humanistic ideals in times of digitalization,” says Stefan. “The support from the City of Vienna is a confirmation for us that we are heading in the right direction.”
Find here the [German] press release by the City of Vienna.
Real data sets are often biased in terms of age, gender or skin color. Many thanks to @kelemam from the @uOttawa for your exciting talk about the advantages of #SyntheticData to avoid #discrimination. pic.twitter.com/TiVuhJQcOC
Real data sets are often biased in terms of age, gender or skin color. Many thanks to @kelemam from the @uOttawa for your exciting talk about the advantages of #SyntheticData to avoid #discrimination. pic.twitter.com/TiVuhJQcOC
Real data sets are often biased in terms of age, gender or skin color. Many thanks to @kelemam from the @uOttawa for your exciting talk about the advantages of #SyntheticData to avoid #discrimination. pic.twitter.com/TiVuhJQcOC