AIROW

We collect and process „big data" from training and performance processes of individual athletes and use state-of-the-art machine learning technology in order to measure effective training load, to predict the effect of training impulses and to optimize training management. It is carried out as a pilot project in cooperation with the Austrian Rowing Federation and will be tailored to the specific needs and conditions in rowing.

Visit for more: airow.univie.ac.at

Transparent and Explainable Models

While the development of algorithms in Data Science has been rapidly evolving, we believe that a crucial component has not deserved enough attention—understanding the use and usability of said algorithms by domain scientists. The methodology of making algorithm usable employed in our grant are interactive visual analysis frameworks. On the algorithmic side, we are constraining ourselves to two important groups of algorithms – clustering as well as neural networks.

Visit for more: vda.cs.univie.ac.at/research/projects/project/341/

Interpretability and Explainability as Drivers to Democracy

More and more decision making in society and politics is supported by intelligent and complex models (ICM). This project explores ways to better engage the electorate in this process by developing interpretable and explainable ICMs and informing the public about how these systems are used.

Visit for more: ml-for-democracy.cs.univie.ac.at/democracy.html

Atlas Galaxia Proxima

A comprehensive catalogue that provides valuable insights into the recent star formation history of our local Milky Way. This projects uses advanced data science methods to construct a high-accuracy master catalog of stellar structures. This catalog will serve as a baseline for further investigations on the fundamental properties of all nearby stellar populations, which provides a unique laboratory for studying star and planet formation and evolution.

Visit for more: galaxia-proxima.univie.ac.at/

SOWINDIC

Due to the alpine characteristics of the Austrian climate, the rotor blades are sometimes significantly iced up at many actual and future locations of wind turbines. The declared aim of this project is to establish an integrated real time data platform with quality assurance for all relevant and available data (icing sensors, weather conditions, meteorological forecasts, market data, etc.). With the prepared data the future production losses of the wind turbines will be estimated and, based on that, an intelligent, preventive rotor blade heating control logic will be developed to minimize the overall icing losses. 

Visit for more: projekte.ffg.at/projekt/4032457

RELEVEN

The aim of RELEVEN is to cast a clearer light on the events of the "short eleventh century" (c. 1030–1095) and specifically to get a better understanding of the ways in which the Christian world was perceived by its inhabitants at the time, particularly in the eastern half of Christendom but also to the north, where the faith had rapidly been expanding.

Visit for more: releven.univie.ac.at