{"id":613,"date":"2026-04-09T13:36:10","date_gmt":"2026-04-09T11:36:10","guid":{"rendered":"https:\/\/wp.unil.ch\/ci26\/?page_id=613"},"modified":"2026-04-15T13:55:35","modified_gmt":"2026-04-15T11:55:35","slug":"posters","status":"publish","type":"page","link":"https:\/\/wp.unil.ch\/ci26\/posters\/","title":{"rendered":"On-Site Poster Presentations"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li>ID5: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID5_WRF%20model%20and%20Meteosat%20with%20Machine%20Learning%20for%20Forecast%20of%20Low%20Stratus%20and%20Fog%20Tested%20on%20a%20Special%20Event.pdf\">WRF model and Meteosat with Machine Learning for Forecast of Low Stratus and Fog Tested on a Special Event (Dorita Rostkier-Edelstein &#8211; Holon Institute of Technology)<\/a><\/li>\n\n\n\n<li>ID6: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID6_Evaluating%20the%20Potential%20of%20Foundation%20Models%20for%20Land%20Use%20and%20Land%20Cover%20Classification.pdf\">Evaluating the Potential of Foundation Models for Land Use and Land Cover Classification (Magali Egger &#8211; Universit\u00e9 de Lausanne)<\/a><\/li>\n\n\n\n<li>ID8: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID8_Physics-informed%20neural%20networks%20predict%20changes%20in%20terrestrial%20water%20storage%20and%20sea%20levels%20better%20than%20climate%20models.pdf\">Physics-informed neural networks predict changes in terrestrial water storage and sea levels better than climate models (Mostafa Kiani Shahvandi &#8211; University of Vienna)<\/a><\/li>\n\n\n\n<li>ID11: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID11_Evaluating%20Finetuned%20Foundation%20Models%20for%20Extreme-Event%20Representation-%20Insights%20from%20Atmospheric%20Rivers.pdf\">Evaluating Finetuned Foundation Models for Extreme-Event Representation: Insights from Atmospheric Rivers (Noelia Otero &#8211; Fraunhofer HHI)<\/a><\/li>\n\n\n\n<li>ID12: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID12_Linking%20BSISO%20Variability%2C%20Extreme%20Rainfall%20in%20the%20Present%20and%20the%20Future.pdf\">Linking BSISO Variability, Extreme Rainfall in the Present and the Future (Aditya Kottapalli &#8211; Indian Institute of Science)<\/a><\/li>\n\n\n\n<li>ID16: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID16_Compounding%20hazards%20increase%20flood%20economic%20losses%20across%20Europe.pdf\">Compounding hazards increase flood economic losses across Europe (Alois Tilloy &#8211; Joint Research Centre of the European Commission)<\/a><\/li>\n\n\n\n<li>ID18: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID18_%20Efficiency%20of%20Machine%20Learning%20Methods%20for%20Extreme%20Precipitation%20Analysis%20.pdf\">Efficiency of Machine Learning Methods for Extreme Precipitation Analysis (Nirajan Dhakal &#8211; Spelman College)<\/a><\/li>\n\n\n\n<li>ID21: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID21_%20A%20Trajectory-Based%20Diagnostic%20Framework%20for%20Convective%20Organization-%20A%20Data-Driven%20Approach%20to%20Monsoon%20Rainfall%20Processes%20.pdf\">A Trajectory-Based Diagnostic Framework for Convective Organization: A Data-Driven Approach to Monsoon Rainfall Processes (Moufeng Wan &#8211; Hong Kong University of Science and Technology)<\/a><\/li>\n\n\n\n<li>ID22: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID22_%20Evaluating%20Spatial%20Generalisation%20of%20Generative%20Downscaling%20.pdf\">Evaluating Spatial Generalisation of Generative Downscaling (Maybritt Schillinger &#8211; ETH Zurich)<\/a><\/li>\n\n\n\n<li>ID23: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID23_ClimaGuard-%20A%20Transparent%20AI%20Framework%20for%20Assessing%20Solar%20Radiation%20Management.pdf\">ClimaGuard: A Transparent AI Framework for Assessing Solar Radiation Management (Philine Bommer &#8211; TU Berlin)<\/a><\/li>\n\n\n\n<li>ID24: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID24_Can%20generative%20AI%20models%20downscale%20very%20rare%20events_%20A%20study%20of%20the%202020%20south%20of%20France%20flash%20flood..pdf\">Can generative AI models downscale very rare events? A study of the 2020 south of France flash flood. (Pierre Chapel &#8211; LMD-IPSL)<\/a><\/li>\n\n\n\n<li>ID25: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID25_Unifying%20context-specific%20causal%20discovery%20in%20the%20PCMCI-framework%20with%20applications%20to%20river%20catchment%20data.pdf\">Unifying context-specific causal discovery in the PCMCI-framework with applications to river catchment data (Wiebke G\u00fcnther &#8211; Technical University Berlin)<\/a><\/li>\n\n\n\n<li>ID28: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID28_Projected%20changes%20in%20the%20Arctic%20sea-ice%20seasonal%20cycle%20inferred%20from%20clustering.pdf\">Projected changes in the Arctic sea-ice seasonal cycle inferred from clustering (Perrine Bauchot; Lab-STICC)<\/a><\/li>\n\n\n\n<li>ID29: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID29_Coupling%20Machine%20Learning%20and%20Data%20Assimilation%20for%20Ocean%20Eddy%20Parameters'%20Prediction.pdf\">Coupling Machine Learning and Data Assimilation for Ocean Eddy Parameters&rsquo; Prediction (Sol\u00e8ne Dealbera &#8211; IMT Atlantique)<\/a><\/li>\n\n\n\n<li>ID31: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID31_Machine%20Learning%20Downscaling%20for%20Wind%20and%20Solar%20Energy%20Drought%20Duration.pdf\">Machine Learning Downscaling for Wind and Solar Energy Drought Duration (Nina Effenberger &#8211; ETH Z\u00fcrich)<\/a><\/li>\n\n\n\n<li>ID32: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID32_How%20can%20climate%20model%20emulators%20be%20aligned%20more%20closely%20with%20the%20needs%20of%20applied%20researchers_.pdf\">How can climate model emulators be aligned more closely with the needs of applied researchers? (Luca Schmidt &#8211; University of T\u00fcbingen)<\/a><\/li>\n\n\n\n<li>ID34: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID34_Attribution%20of%20Pacific%20trend%20discrepancies%20using%20the%20Forced%20Component%20Estimation%20Statistical%20Method%20Intercomparison%20Project%20(ForceSMIP).pdf\">Attribution of Pacific trend discrepancies using the Forced Component Estimation Statistical Method Intercomparison Project (ForceSMIP) (Robert Jnglin Wills &#8211; ETH Zurich)<\/a><\/li>\n\n\n\n<li>ID37: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID37_Diffusion%20Models%20for%20Generative%20Emulation%20of%20Regional%20Climate%20Models-%20Simulating%20Downscaling%20Uncertainty.pdf\">Diffusion Models for Generative Emulation of Regional Climate Models: Simulating Downscaling Uncertainty (Mikel Legasa &#8211; LSCE-IPSL)<\/a><\/li>\n\n\n\n<li>ID42: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID42_Learning%20Spatiotemporal%20Precipitation%20Fields%20with%20Probabilistic%20Neural%20Processes.pdf\">Learning Spatiotemporal Precipitation Fields with Probabilistic Neural Processes (Pritthijit Nath &#8211; University Of Cambridge)<\/a><\/li>\n\n\n\n<li>ID44: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID44_Spatially-contiguous%20reconstruction%20of%20water%20temperature%20and%20discharge%20in%20Switzerland%20using%20deep%20learning.pdf\">Spatially-contiguous reconstruction of water temperature and discharge in Switzerland using deep learning (Louis Poulain&#8211;Auz\u00e9au &#8211; ETH Z\u00fcrich)<\/a><\/li>\n\n\n\n<li>ID48: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID48_Sim2Real%20Conditional%20Diffusion%20for%20Radar%20Beam%20Blockage%20Correction-%20A%20Preliminary%20Study.pdf\">Sim2Real Conditional Diffusion for Radar Beam Blockage Correction: A Preliminary Study (Assaad Zeghina &#8211; Latmos Lab)<\/a><\/li>\n\n\n\n<li>ID51: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID51_Simulating%20riverine%20heatwaves-%20a%20European%20reconstruction%20of%20river%20temperatures%20with%20an%20LSTM.pdf\">Simulating riverine heatwaves: a European reconstruction of river temperatures with an LSTM (Corinna Frank &#8211; ETH Zurich)<\/a><\/li>\n\n\n\n<li>ID52: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID52_Machine%20Learning%20Estimation%20of%20Arctic%20Sea%20Ice%20Thickness%20Distribution%20in%20Coarse-Resolution%20Ocean%20Models%20Trained%20with%20High-Resolution%20Satellite%20Data.pdf\">Machine Learning Estimation of Arctic Sea Ice Thickness Distribution in Coarse-Resolution Ocean Models Trained with High-Resolution Satellite Data (L\u00e9o Edel &#8211; NERSC)<\/a><\/li>\n\n\n\n<li>ID57: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID57_Evaluation%20of%20Deep%20Learning%20Models%20for%20Satellite%20IR%20Precipitation%20Estimation.pdf\">Evaluation of Deep Learning Models for Satellite IR Precipitation Estimation (Matthieu Meignin &#8211; LATMOS\/UVSQ)<\/a><\/li>\n\n\n\n<li>ID61: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID61_Adaptive%20regionalization%20for%20extreme%20precipitation-%20A%20neural%20network-weighted%20independence%20likelihood%20approach.pdf\">Adaptive regionalization for extreme precipitation: A neural network-weighted independence likelihood approach (Robert Paulus &#8211; UCLouvain)<\/a><\/li>\n\n\n\n<li>ID62: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID62_Topography-aware%20Temperature%20Forecasting%20in%20Europe.pdf\">Topography-aware Temperature Forecasting in Europe (<br>Chang Xu &#8211; EPFL)<\/a><\/li>\n\n\n\n<li>ID65: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID65_Multi-source%20cross-sensor%20harmonization%20via%20generative%20self-supervised%20learning.pdf\">Equivariance-based self-supervised learning and SAR tomography for monitoring forest structures (Zoe Berenger &#8211; Telecom Paris)<\/a><\/li>\n\n\n\n<li>ID70: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID70_Charting%20the%20unseen%20%E2%80%93%20A%20journey%20into%20disaster%20displacement%20risk.pdf\">Charting the unseen \u2013 A journey into disaster displacement risk (Maxime Souvignet &#8211; UNU-EHS)<\/a><\/li>\n\n\n\n<li>ID72: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID72_End-to-end%20learning%20from%20simulated%20observations%20for%20the%20neural%20mapping%20of%20real%20altimetry%20data.pdf\">End-to-end learning from simulated observations for the neural mapping of real altimetry data (Daniel Zhu &#8211; IMT Atlantique)<\/a><\/li>\n\n\n\n<li>ID75: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID75_Statistical%20downscaling%20for%20precipitation%20examinating%20potential%20temporal%20dependence%20due%20to%20climate%20change.pdf\">Statistical downscaling for precipitation examinating potential temporal dependence due to climate change (Weixi Sun &#8211; Centralesupelec, L2S Laboratory)<\/a><\/li>\n\n\n\n<li>ID76: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID76_Integrating%20a%20ML-enhanced%20Radiation%20Parameterization%20into%20ICON-XPP.pdf\">Integrating a ML-enhanced Radiation Parameterization into ICON-XPP (Katharina Hafner &#8211; University of Bremen)<\/a><\/li>\n\n\n\n<li>ID77: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID77_A%20Machine%20Learning%20approach%20to%20study%20the%20ocean-atmosphere%20interactions%20in%20CESM2%20for%20the%20North%20Atlantic.pdf\">A Machine Learning approach to study the ocean-atmosphere interactions in CESM2 for the North Atlantic (Clara Wetzel &#8211; EPFL)<\/a><\/li>\n\n\n\n<li>ID78: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID78_Evaluating%20ArchesWeather%20and%20ArchesWeatherGen%20under%20Multi-Decadal%20AMIP-style%20climate%20simulations.pdf\">Evaluating ArchesWeather and ArchesWeatherGen under Multi-Decadal AMIP-style climate simulations (Renu Singh &#8211; Google Deepmind \/ INRIA France)<\/a><\/li>\n\n\n\n<li>ID80: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID80_Hybrid%20dynamical-statistical%20modelling%20of%20the%20North%20Atlantic%20climate.pdf\">Hybrid dynamical-statistical modelling of the North Atlantic climate (Elena Provenzano &#8211; LOCEAN (IPSL))<\/a><\/li>\n\n\n\n<li>ID89: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID89_Tracks%20for%20Enhancing%20Rainfall-Induced%20Landslide%20Prediction.pdf\">Tracks for Enhancing Rainfall-Induced Landslide Prediction (Jacques Soutter &#8211; UNIL)<\/a><\/li>\n\n\n\n<li>ID90: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID90_SVD-ROM-%20Scalable%20Reduced-Order%20Modeling%20of%20Weather%20and%20Climate%20Data%20Using%20the%20Singular%20Value%20Decomposition.pdf\">SVD-ROM: Scalable Reduced-Order Modeling of Weather and Climate Data Using the Singular Value Decomposition (David Salvador-Jasin &#8211; The Alan Turing Institute)<\/a><\/li>\n\n\n\n<li>ID93: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID93_Towards%20a%20distributional%20autoencoder%20for%20climate%20counterfactuals.pdf\">Towards a distributional autoencoder for climate counterfactuals (Frieder Loer &#8211; Institute for Meteorology, Leipzig University)<\/a><\/li>\n\n\n\n<li>ID98: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID98_GOES-ABI%20Data%20Cube-%20Unifying%20Eight%20Years%20of%20Geostationary%20Satellite%20Observations.pdf\">GOES-ABI Data Cube: Unifying Eight Years of Geostationary Satellite Observations (Mickell Als &#8211; University of Toronto)<\/a><\/li>\n\n\n\n<li>ID108: <a href=\"https:\/\/github.com\/freddy0218\/ClimateInformatics2026\/blob\/main\/Extended_Abstract\/ID108_Seeing%20the%20Air-%20Social%20Media%20Imagery%20for%20Seasonal%20Air%20Quality%20Monitoring%20in%20a%20Himalayan%20Valley%20City.pdf\">Seeing the Air: Social Media Imagery for Seasonal Air Quality Monitoring in a Himalayan Valley City (Bhavya S &#8211; TERI SAS)<\/a><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1002254,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"template-full-width.php","meta":{"_seopress_robots_primary_cat":"","_seopress_titles_title":"","_seopress_titles_desc":"","_seopress_robots_index":"","footnotes":""},"class_list":["post-613","page","type-page","status-publish","has-post-thumbnail"],"_links":{"self":[{"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/pages\/613","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/users\/1002254"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/comments?post=613"}],"version-history":[{"count":3,"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/pages\/613\/revisions"}],"predecessor-version":[{"id":630,"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/pages\/613\/revisions\/630"}],"wp:attachment":[{"href":"https:\/\/wp.unil.ch\/ci26\/wp-json\/wp\/v2\/media?parent=613"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}