Daniel Klotz

Short bio:

Daniel Klotz is an assistant professor from IT:U Ausstria. works on the intersection between machine learning and earth science. In his research he focuses on developing and applying data-driven approaches for understanding, describing and reducing environmental risks. In short, the focus is on applied, cutting edge research developed in close relationship with real world applications. For example, a specific focus are hydrological phenomena such as floods and droughts — natural hazards that have severe impact on human lives. Floods are associated with high-rainfall intensities and can often happen in very short times. Droughts have a much larger spatial and temporal extent (that can persist over several years). Machine learning provides an avenue to develop comprehensive hydrological modeling approaches with the ability to depict the required scales across time and space.