I lead an interdisciplinary research group in data science at the Institute for Ecological Economics, WU Vienna. Supported by competitive national and international funding, most notably an ERC Consolidator Grant, my work advances spatial analytics and AI methods by developing new algorithms and software that scale to global datasets. These tools transform raw data into spatially explicit environmental metrics, strengthening the foundations of emerging Earth Intelligence systems. Among my key contributions are the development of the Time-Weighted Dynamic Time Warping (TWDTW) algorithm for time series classification and pioneering global-scale assessments of mine-specific impacts that reveal critical, previously overlooked knowledge in the sector’s environmental footprints. By focusing on methodological innovation with real-world applications, my team provides the essential tools and empirical insights needed to monitor global environmental change and support evidence-based sustainability decisions.
A data-driven approach to mapping global commodity-specific mining land-use, Journal of Cleaner Production (2026)
An update on global mining land use, Scientific Data (2022)
A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2016)