Michele Volpi

Lead Data Scientist | Climate & Environment Domain Lead

Research

(Alumni)

Michele Volpi holds a Ph.D. in Environmental Sciences from the University of Lausanne (2013). He was a postdoctoral researcher in the CALVIN group at the University of Edinburgh’s School of Informatics (2014–2016), and then a member of the Multimodal Remote Sensing and Geocomputation groups at the University of Zurich’s Department of Geography (2016–2017). He joined SDSC in 2018 as Senior Data Scientist in the Research Team and became Lead Data Scientist in 2022. Since 2025, Michele serves as Climate and Environment Domain Lead, overseeing SDSC’s activities in this area. He leads projects in geospatial machine learning, working with Earth observation and geolocated spatio-temporal data, with applications in climate and weather, ecology, natural hazards, and agriculture, among others. Michele is also a Lecturer in the Department of Environmental Systems Sciences at ETH Zurich.

Projects

ECOCLIM

In Progress

Integrating ecological information into climate downscaling

Academia

BioAIRad

In Progress

Biodiversity monitoring of the AIrspace with Radars

Academia

SPI-GreenFjord

In Progress

Academia

SPI-PAMIR

In Progress

Academia

Fore[st]cast

In Progress

Nowcast and predict forest condition

Academia

BioDetect

Completed

Deep Learning for Biodiversity Detection and Classification

Academia

Inter-Detect

In Progress

Quantifying Plant-Pollinator Interactions Using Computer Vision

Academia

DNAi

Completed

High throughput eDNA processing using artificial intelligence for ecosystem monitoring

Academia

PHENO-MINE

Completed

Pheno-Mine: Extracting dynamic ideotypes from seasonal image time series of wheat taken in the field

Academia

DATSSFLOW

Completed

Data Science and Mass Movement Seismology: Towards the Next Generation of Debris Flow Warning

Academia

DIMPEO

Completed

Detecting drought impacts on forests in earth observation data

Academia

SPEED2ZERO

In Progress

Sustainable pathways towards net zero Switzerland

Academia

EAGLE

In Progress

Enhanced understanding of Alpine mass movements Gathered through machine LEarning

Academia

ADOPT

Completed

AI for Detecting Ocean Plastic Pollution with Tracking

Academia

DeepDown

Completed

Multivariate climate downscaling using deep learning models

Academia

CLIMIS4AVAL

Completed

Real-time cleansing of snow and weather data for operational avalanche forecasting

Academia

deepLNAfrica

Completed

Mapping changes in urban informal settlements in sub-Saharan Africa using deep learning and open-access satellite imagery

Academia

ArcticNAP

Completed

Arctic climate change: Exploring the Natural Aerosol baseline for improved model Predictions

Academia

DEAPSnow

Completed

Improving snow avalanche forecasting by data-driven automated predictions

Academia

MSEI

Completed

Molecular structure elucidation by integrating different data mining strategies

Academia

ACE-DATA

Completed

Delivering Added-value To Antarctica

Academia

Publications

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Law, S.; Horinouchi, M.; Suel, E.; Stalder, S.; Volpi, M.; Shen, Y.; Li, M.; Takizawa, A. "Estimating and mapping Tokyo Window View Desirability using 3D model imagery and the hedonic price approach" Applied Geography 194 104110 2026 View publication 

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Kamper, F.; Walter, F.; Paitz, P.; Meyer, M.; Volpi, M.; Salzmann, M. "Exploring seismic mass-movement data with anomaly detection and dynamic time warping" Preprint 2025 View publication 

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Simeon, A.; Pérez-Guillén, C.; Volpi, M.; Seupel, C.; Van Herwijnen, A. "Autoencoder-based feature extraction for the automatic detection of snow avalanches in seismic data" Geoscientific Model Development 18 22 8751-8776 2025 View publication 

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Stalder, S.; Sanchez, T.; Volpi, M.; Manel, S.; Mouillot, D.; Auber, A.; Bruno, M.; Marques, V.; Albouy, C.; Pellissier, L.; et al. "Zero-shot deep learning for the annotation of unknown eDNA sequences using co-occurrences and phylogenetic embeddings" PLOS Computational Biology 21 12 e1013776 2025 View publication 

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Gajardo, J.; Volpi, M.; Onwude, D.; Defraeye, T. "Evaluating the role of training data origin for country-scale cropland mapping in data-scarce regions: A case study of Nigeria" ISPRS Open Journal of Photogrammetry and Remote Sensing 17 100091 2025 View publication 

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Lamperti, L.; Sanchez, T.; Stalder, S.; Mouillot, D.; Volpi, M.; Albouy, C.; Bruno, M.; Molin, N.; Francois, O.; Manel, S.; et al. "End-to-End Artificial Learning of Protection Gradient from Raw eDNA Sequences" Preprint 2025 View publication 

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Wang, R.; Ziegler, M.; Volpi, M.; Manconi, A. "Advanced identification of geological discontinuities with deep learning" Applied Computing and Geosciences 100256 2025 View publication 

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Sanchez, T.; Stalder, S.; Lamperti, L.; Brosse, S.; Frossard, A.; Leugger, F.; Rozanski, R.; Zong, S.; Manel, S.; Medici, L.; et al. "<span style="font-variant:small-caps;">ORDNA</span> : Deep‐learning‐based ordination for raw environmental <span style="font-variant:small-caps;">DNA</span> samples" Methods in Ecology and Evolution 2041-210X.70033 2025 View publication 

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Büttner, N.; Stalder, S.; Volpi, M.; Suel, E.; Harttgen, K. "Large-scale slum mapping in sub-Saharan Africa's major cities: Remote sensing and deep learning reveal strong slum growth in the urban periphery between 2016 and 2022" Habitat International 161 2025 View publication 

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Pérez-Guillén, C.; Techel, F.; Volpi, M.; Van Herwijnen, A. "Assessing the performance and explainability of an avalanche danger forecast model" Natural Hazards and Earth System Sciences 25 4 1331-1351 2025 View publication 

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Samarin, M.; Horton, P.; Otero, N.; Allen, S.; Volpi, M. "Assessment of Local Climate Impact through Multivariate Downscaling Using Deep Learning" EXCLAIM Symposium 2025 View publication 

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Horton, P.; Samarin, M.; Otero, N.; Allen, S.; Volpi, M. "Multivariate climate downscaling using deep learning models" EGU General Assembly 2025 View publication 

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Dalsasso, E.; Russwurm, M.; Donner, C.; De Vries, R.; Volpi, M.; Tuia, D. "A cross-sensor approach for marine litter detection with self-supervised learning" EGU General Assembly 2025 2025 View publication 

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Goshtasbpour, S.; Samarin, M.; Volpi, M. "Learning Extreme Temperature Regimes" ICLR 2025 Workshop on Tackling Climate Change with Machine Learning 2025 View publication 

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Donner, C.; Goshtasbpour, S.; Dalsasso, E.; Volpi, M.; Russwurm, M.; Tuia, D. "Autoregressive denoising diffusion for predicting trajectories of floating objects in oceans" EGU General Assembly 2025 2025 View publication 

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Svoboda, J.; Ruesch, M.; Liechti, D.; Jones, C.; Volpi, M.; Zehnder, M.; Schweizer, J. "Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)" Geoscientific Model Development 18 5 1829-1849 2025 View publication 

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Maier, K.; Bernhard, P.; Ly, S.; Volpi, M.; Nitze, I.; Li, S.; Hajnsek, I. "Detecting mass wasting of Retrogressive Thaw Slumps in spaceborne elevation models using deep learning" International Journal of Applied Earth Observation and Geoinformation 137 104419 2025 View publication 

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Boyd Pernov, J.; Aeberhard, W. H.; Volpi, M.; Harris, E.; Hohermuth, B.; Ishino, S.; Henne, S.; Im, U.; Quinn, P. K.; Upchurch, L. M.; et al. "Data-driven modeling of environmental factors influencing Arctic methanesulfonic acid aerosol concentrations" Atmospheric Chemistry and Physics 2025 View publication 

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Stalder, S.; Volpi, M.; Büttner, N.; Law, S.; Harttgen, K.; Suel, E. "Self-supervised learning unveils urban change from street-level images" Computers, Environment and Urban Systems 112 102156 2024 View publication 

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Boyd Pernov, J.; Harris, E.; Volpi, M.; Baumgartner, T.; Hohermuth, B.; Henne, S.; Aeberhard, W. H.; Becagli, S.; Quinn, P. K.; Traversi, R.; et al. "Pan-Arctic Methanesulfonic Acid Aerosol: Source regions, atmospheric drivers, and future projections" npj Climate and Atmospheric Science 7 166 1-18 2024 View publication 

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Maissen, A.; Techel, F.; Volpi, M. "A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting" Geoscientific Model Development 17 21 7569-7593 2024 View publication 

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Gomes, D.; Purves, R. S.; Volpi, M. "Fine-Tuning Transformers for Toponym Resolution: A Contextual Embedding Approach to Candidate Ranking." GeoExT@ ECIR 43–51 2024 View publication 

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Simeon, A.; Pérez-Guillén, C.; Volpi, M.; Seupel, C.; Van Herwijnen, A. "Assessing avalanche activity in seismic data with modern machine learning methods." 2024 View publication 

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Svoboda, J.; Zehnder, M.; Ruesch, M.; Liechti, D.; Jones, C.; Volpi, M.; Rixen, C.; Schweizer, J. "Classification of Snow Depth Measurements for tracking plant phenological shifts in Alpine regions" NeurIPS 2024 Workshop on Tackling Climate Change with Machine Learning 2024 View publication 

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Hendrick, M.; Techel, F.; Volpi, M.; Olevski, T.; Pérez-Guillén, C.; Herwijnen, A. V.; Schweizer, J. "Automated prediction of wet-snow avalanche activity in the Swiss Alps" Journal of Glaciology 69 277 1365-1378 2023 View publication 

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Paitz, P.; Chmiel, M.; Husmann, L.; Volpi, M.; Kamper, F.; Walter, F. "Towards an unsupervised generic seismic detector for hazardous mass-movements: a data-driven approach" 2023 View publication 

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Paitz, P.; Chmiel, M.; Husmann, L.; Volpi, M.; Kamper, F.; Walter, F. "Generic seismic mass-movement detection leveraging unsupervised statistical learning methods" Machine Learning in Geo-, Ocean and Space Sciences. IUGG General Assembly IUGG23-0742 2023 View publication 

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Pérez-Guillén, C.; Seupel, C.; Simeon, A.; Volpi, M.; van Herwijnen, A. "Automated discrimination of seismo-acoustic avalanche signals" EGU General Assembly Conference Abstracts EGU23-12211 2023 View publication 

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Harris, E.; Gasser, L.; Volpi, M.; Perez-Cruz, F.; Bjelić, S.; Obozinski, G. "Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry" Structural Chemistry 34 5 1935-1950 2023 View publication 

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Roškar, R.; Ramakrishnan, C.; Volpi, M.; Perez-Cruz, F.; Alisafaee, M.; Fischer, P.; Gasser, L.; Harris, E. J.; Ozdemir, F.; Paitz, P.; et al. "Renku: a platform for sustainable data science" Proceedings of the 37th International Conference on Neural Information Processing Systems 42161–42173 2023 View publication 

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Li, D.; Gajardo, J.; Volpi, M.; Defraeye, T. "Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region" Remote Sensing Applications: Society and Environment 101057 2023 View publication 

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Pérez-Guillén, C.; Techel, F.; Hendrick, M.; Volpi, M.; van Herwijnen, A.; Olevski, T.; Obozinski, G.; Pérez-Cruz, F.; Schweizer, J. "Weather, snowpack and danger ratings data for automated avalanche danger level predictions" Available at: https://www.doi.org/10.16904/envidat.330 2022 View publication 

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Hendrick, M.; Techel, F.; Volpi, M.; Olevski, T.; Pérez-Guillén, C.; van Herwijnen, A.; Schweizer, J. "Automated prediction of wet-snow avalanche activity in Switzerland" EGU General Assembly Conference Abstracts EGU22-7403 2022 View publication 

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Pérez-Guillén, C.; Techel, F.; Hendrick, M.; Volpi, M.; van Herwijnen, A.; Olevski, T.; Obozinski, G.; Pérez-Cruz, F.; Schweizer, J. "Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland" Natural Hazards and Earth System Sciences 22 2031–2056 2022 View publication 

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Stalder, S.; Perraudin, N.; Achanta, R.; Perez-Cruz, F.; Volpi, M. "What You See is What You Classify: Black Box Attributions" Neural Information Processing Systems (NeurIPS) 2022 View publication 

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Hartmann, M. C.; Schott, M.; Dsouza, A.; Metz, Y.; Volpi, M.; Purves, R. S. "A text and image analysis workflow using citizen science data to extract relevant social media records: Combining red kite observations from Flickr, eBird and iNaturalist" Ecological Informatics 71 101782 2022 View publication 

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Landwehr, S.; Volpi, M.; Haumann, F. A.; Robinson, C. M.; Thurnherr, I.; Ferracci, V.; Baccarini, A.; Thomas, J.; Gorodetskaya, I.; Tatzelt, C.; et al. "Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition" Earth System Dynamics 12 4 1295-1369 2021 View publication 

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Pegoraro, L.; Volpi, M.; Matthews, B.; Graham, C. "BioDetect: automated image processing for ecological monitoring" 50th Annual Meeting of the Ecological Society of Germany, Austria and Switzerland 2021 View publication 

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Thomas, J.; Alba, M.; Bouillet, E.; Novellino, A.; Pina Estany, C.; Volpi, M. "How to stop re-inventing the wheel: a data management case study" International Conference on Marine Data and Information Systems 2021 View publication 

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Pérez-Guillén, C.; Hendrick, M.; Techel, F.; van Herwijnen, A.; Volpi, M.; Olevski, T.; Pérez-Cruz, F.; Obozinski, G.; Schweizer, J. "Data-driven automatic predictions of avalanche danger in Switzerland" EGU General Assembly Conference Abstracts EGU21–6154 2021 View publication 

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Roscher, R.; Volpi, M.; Mallet, C.; Drees, L.; Wegner, J. D. "SemCity Toulouse: A benchmark for building instance segmentation in satellite images" ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-5-2020 109-116 2020 View publication 

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Landwehr, S.; Volpi, M.; Derkani, M. H.; Nelli, F.; Alberello, A.; Toffoli, A.; Gysel-Beer, M.; Modini, R. L.; Schmale, J. "Sea State and Boundary Layer Stability Limit Sea Spray Aerosol Lifetime over the Southern Ocean" Preprint 2020 View publication 

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Volpi, M.; Landwehr, S.; Thomas, J.; Schmale, J. "ERA-5 reanalysis results interpolated onto the five-minute average cruise track of the Antarctic Circumnavigation Expedition (ACE) during the austral summer of 2016/2017" Available at: http://dx.doi.org/10.5281/zenodo.3831980 2020 View publication 

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Volpi, M.; Landwehr, S.; Thomas, J.; Schmale, J. "Distance to the nearest land/coastline (including small subantarctic islands) for the five-minute average cruise track of the Antarctic Circumnavigation Expedition (ACE) during the austral summer of 2016/2017" Available at: http://dx.doi.org/10.5281/zenodo.3832045 2020 View publication 

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Landwehr, S.; Volpi, M.; Perez-Cruz, F.; Schmale, J. "Sparse Principal Component Analysis as a tool for the exploration of heterogeneous datasets from multidisciplinary field experiments" Data Science in Climate and Climate Impact Research 2020 View publication 

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Acheson, E.; Volpi, M.; Purves, R. S. "Machine learning for cross-gazetteer matching of natural features" International Journal of Geographical Information Science 34 4 708-734 2020 View publication 

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Roth, S. I.; Leiterer, R.; Volpi, M.; Celio, E.; Schaepman, M. E.; Joerg, P. C. "Automated detection of individual clove trees for yield quantification in northeastern Madagascar based on multi-spectral satellite data" Remote Sensing of Environment 221 144-156 2019 View publication 

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Landwehr, S.; Modini, R.; Schmale, J.; Volpi, M.; Toffoli, A.; Thurnherr, I.; Aemisegger, F.; Wernli, H. "Investigation of sea spray source functions with remote ocean aerosol size spectra measurements from the Antarctic Circumnavigation Experiment" SOLAS open science conference 2019 View publication 

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Thomas, J.; Landwehr, S.; Volpi, M.; Schmale, J. "ACE-DATA: Antarctic Circumnavigation Expedition – Delivering Added value To Antarctica (Version 1.0)" Preprint 2019 View publication 

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Volpi, M. "Semantic interpretation of optical remote sensing data by computer vision and machine learning" Keynote talk at Applied Machine Learning Days (AMLD), Lausanne (CH) 2019 View publication 

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Volpi, M.; Tuia, D. "Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images" ISPRS Journal of Photogrammetry and Remote Sensing 144 48-60 2018 View publication 

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Wegner, J. D.; Roscher, R.; Volpi, M.; Veronesi, F. "Foreword to the Special Issue on Machine Learning for Geospatial Data Analysis" ISPRS International Journal of Geo-Information 7 147 2018 View publication 

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Milani, G.; Volpi, M.; Tonolla, D.; Doering, M.; Robinson, C.; Kneubühler, M.; Schaepman, M. "Robust Quantification of Riverine Land Cover Dynamics by High-Resolution Remote Sensing" Remote Sensing of Environment 217 491-505 2018 View publication 

Mentioned in

May 20, 2025

Enhancing Environmental Data Interoperability Across the ETH Domain

Insights from the “ENRICH/SDSC Data Workshop: Interoperability of Environmental Data and AI” that took place on May 6, 2025 at Eawag.

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November 4, 2024

MeteoSwiss and the SDSC join forces

The Federal Office of Meteorology and Climatology (MeteoSwiss) and the Swiss Data Science Center have signed a framework agreement.

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March 6, 2024

RAvaFcast | Automating regional avalanche danger prediction in Switzerland

RAvaFcast is a data-driven model pipeline developed for automated regional avalanche danger forecasting in Switzerland.

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November 30, 2023

La Liberté | AI to better detect plastic waste at sea [In French]

Scientists at EPFL and Wageningen University have developed an AI model that recognizes plastic objects floating on water in satellite images.

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November 30, 2023

A simple dashboard facilitates the work of parliamentary services

The SDSC has developed a dashboard for parliamentary services to calculate the composition of the committees of the National Council.

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October 31, 2023

Street2Vec | Self-supervised learning unveils change in urban housing from street-level images

It is difficult to effectively monitor and track progress in urban housing. We attempt to overcome these limitations by utilizing self-supervised learning with over 15 million street-level images taken between 2008 and 2021 to measure change in London.

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October 25, 2023

Computerworld | AI predicts avalanche danger [In German]

The AI project "DEAPSnow" takes avalanche forecasting to a whole new level.

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October 9, 2023

DEAPSnow | AI for avalanche forecasting

“DEAPSnow”, a project by the Swiss Data Science Center (SDSC) and the WSL Institute for Snow and Avalanche Research SLF, developed an Artificial Intelligence (AI) to support avalanche forecasters in creating the avalanche bulletin. This product provides essential information about the prevailing snow and avalanche conditions in the Swiss Alps and the Jura.

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September 23, 2022

What you see is what you classify: black box attributions

The lack of transparency of black-box models is a fundamental problem in modern Artificial Intelligence and Machine Learning. This work focuses on how to unbox deep learning models for image classification problems.

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October 28, 2021

DEAPSnow | Supporting avalanche forecasting in the Swiss Alps using machine learning

The creation of avalanche bulletins is still a largely expert-driven and manual task. DEAPSnow aims to explore the feasibility of using data-driven models to support the process of avalanche danger forecast.

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May 2, 2019

ACE-DATA | Antarctic circumnavigation expedition – delivering added value to Antarctica

Understanding the complexity of the Earth systems and our climate is important to be able to make predictions about how they may change in the future. To do this, scientists use models which describe the relevant processes.

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Case Studies

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