Rate My Professor Ashok Dahal

Ashok Dahal is an Assistant Professor in the Faculty of Geo-Information Science and Earth Observation at the University of Twente, affiliated with the ITC-GAIA department within the Scientific Departments. Hailing from the mountains of Nepal, where he witnessed the devastating effects of earthquakes, landslides, wildfires, and floods, Dahal developed a keen interest in natural hazards. He holds a Bachelor's degree in Geomatics Engineering from Tribhuvan University and completed both his MSc and PhD at the University of Twente. His PhD research centered on Geophysical and Geo-AI-based evaluation and modelling of earthquake-induced landslides, under the supervision of prominent researchers in the field. In his current position, Dahal leads research projects exploring multi-hazard interactions, supervises MSc and PhD students, and teaches courses such as TE II: GeoAI and data-driven modeling. His work emphasizes the integration of physics, mathematics, programming, and earth sciences to advance predictive capabilities for geohazards.

Dahal's research expertise lies at the intersection of geomatics, remote sensing, and artificial intelligence, focusing on monitoring hazards with satellite and geospatial data and enhancing modelling through AI techniques. He has received the EscherPrijs in 2021 and the ITC Publication Award in 2023 for his contributions. Notable publications include "Quantifying the influence of topographic amplification on the landslides triggered by the 2015 Gorkha earthquake" (Communications Earth & Environment, 2024), "At the junction between deep learning and statistics of extremes: Formalizing the landslide hazard definition" (Journal of Geophysical Research: Machine Learning and Computation, 2024), "Towards physics-informed neural networks for landslide prediction" (Engineering Geology, 2025), "Distribution-agnostic landslide hazard modelling via Graph Transformers" (Environmental Modelling & Software, 2025), "Long and short-term perspectives on space–time landslide modelling" (International Journal of Applied Earth Observation and Geoinformation, 2025), and "Pan-European landslide risk assessment: From theory to practice" (Reviews of Geophysics, 2025). Dahal has collaborated with international institutions, including NASA's Jet Propulsion Laboratory, to develop remote sensing methods for natural hazards, create open datasets, and offer courses on AI applications in hazard modeling. With 50 research outputs encompassing 22 articles, 12 preprints, and 6 datasets, his scholarship supports UN Sustainable Development Goals related to industry innovation, infrastructure, and climate action.