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Raphael Huser. Completed the Doctor of Philosophy in Statistics in 2013/09/14 by École Polytechnique Fédérale de Lausanne, Master in Applied Mathematics in 2009/02/15 by École Polytechnique Fédérale de Lausanne and Bachelor in Mathematics in 2007/07/15 by École Polytechnique Fédérale de Lausanne. Is Associate Professor in King Abdullah University of Science and Technology. Published 71 articles in journals. Has 1 section(s) of books. Has received 6 awards and/or honors. Works in the area(s) of Exact Sciences with emphasis on Mathematics with emphasis on Statistics and Probability, Exact Sciences with emphasis on Mathematics with emphasis on Statistics and Probability and Exact Sciences with emphasis on Mathematics with emphasis on Statistics and Probability.
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Identificação

Identificação pessoal

Nome completo
Raphael Huser

Nomes de citação

  • Huser, Raphael

Identificadores de autor

Ciência ID
C514-7AF1-039E
ORCID iD
0000-0002-1228-2071

Websites

Domínios de atuação

  • Ciências Exatas - Matemática - Estatística e Probabilidades
  • Ciências Exatas - Matemática - Estatística e Probabilidades
  • Ciências Exatas - Matemática - Estatística e Probabilidades

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Francês (Idioma materno)
Inglês Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2) Utilizador proficiente (C2)
Formação
Grau Classificação
2009/02/15 - 2013/09/14
Concluído
 Statistics (Doctor of Philosophy)
École Polytechnique Fédérale de Lausanne, Suiça
"Statistical modeling and inference for spatio-temporal extremes" (TESE/DISSERTAÇÃO)
2007/09/15 - 2009/02/15
Concluído
 Applied Mathematics (Master)
École Polytechnique Fédérale de Lausanne, Suiça
"On kriging of extreme precipitation return levels and tapering" (TESE/DISSERTAÇÃO)
2004/09/15 - 2007/07/15
Concluído
 Mathematics (Bachelor)
École Polytechnique Fédérale de Lausanne, Suiça
Percurso profissional

Docência no Ensino Superior

Categoria Profissional
Instituição de acolhimento 		Empregador
2022/07/01 - Atual Professor Associado (Docente Universitário) King Abdullah University of Science and Technology, Arábia Saudita
2015/03/15 - 2022/06/30 Professor Auxiliar (Docente Universitário) King Abdullah University of Science and Technology, Arábia Saudita

Cargos e Funções

Categoria Profissional
Instituição de acolhimento 		Empregador
2013/12/28 - 2015/03/14 Postdoctoral Research Fellow King Abdullah University of Science and Technology, Arábia Saudita
Produções

Publicações

Artigo em revista
  1. Raphaël Huser; Andrew Zammit-Mangion. "R Huser and A Zammit-Mangion’s contribution to the Discussion of the ‘Discussion Meeting on the Analysis of citizen science data’". Journal of the Royal Statistical Society Series A: Statistics in Society (2025): https://doi.org/10.1093/jrsssa/qnaf012.
    10.1093/jrsssa/qnaf012
  2. Raphaël Huser; Thomas Opitz; Jennifer L. Wadsworth. "Modeling of spatial extremes in environmental data science: time to move away from max-stable processes". Environmental Data Science (2025): https://doi.org/10.1017/eds.2024.54.
    10.1017/eds.2024.54
  3. Arnab Hazra; Raphaël Huser; David Bolin. "Efficient Modeling of Spatial Extremes over Large Geographical Domains". Journal of Computational and Graphical Statistics (2024): https://doi.org/10.1080/10618600.2024.2409784.
    10.1080/10618600.2024.2409784
  4. Silius M Vandeskog; Raphaël Huser; Oddbjørn Bruland; Sara Martino. "Fast spatial simulation of extreme high-resolution radar precipitation data using integrated nested Laplace approximations". Journal of the Royal Statistical Society Series C: Applied Statistics (2024): https://doi.org/10.1093/jrsssc/qlae074.
    10.1093/jrsssc/qlae074
  5. Raphaël Huser. "Seconder of the vote of thanks to Healy et al. and contribution to the Discussion of “Inference for extreme spatial temperature events in a changing climate with application to Ireland”". Journal of the Royal Statistical Society Series C: Applied Statistics (2024): https://doi.org/10.1093/jrsssc/qlae078.
    10.1093/jrsssc/qlae078
  6. Matthew Sainsbury-Dale; Andrew Zammit-Mangion; Jordan Richards; Raphaël Huser. "Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks". Journal of Computational and Graphical Statistics (2024): https://doi.org/10.1080/10618600.2024.2433671.
    10.1080/10618600.2024.2433671
  7. Peng Zhong; Manuela Brunner; Thomas Opitz; Raphaël Huser. "Spatial Modeling and Future Projection of Extreme Precipitation Extents". Journal of the American Statistical Association (2024): https://doi.org/10.1080/01621459.2024.2408045.
    10.1080/01621459.2024.2408045
  8. Xuanjie Shao; Arnab Hazra; Jordan Richards; Raphaël Huser. "Flexible Modeling of Nonstationary Extremal Dependence using Spatially Fused LASSO and Ridge Penalties". Technometrics (2024): https://doi.org/10.1080/00401706.2024.2388549.
    10.1080/00401706.2024.2388549
  9. Ashok Dahal; Raphaël Huser; Luigi Lombardo. "At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition". Journal of Geophysical Research: Machine Learning and Computation (2024): https://doi.org/10.1029/2024JH000164.
    10.1029/2024JH000164
  10. Raphaël Huser; Michael L. Stein; Peng Zhong. "Vecchia Likelihood Approximation for Accurate and Fast Inference with Intractable Spatial Max-Stable Models". Journal of Computational and Graphical Statistics (2024): https://doi.org/10.1080/10618600.2023.2285332.
    10.1080/10618600.2023.2285332
  11. Yan Gong; Peng Zhong; Thomas Opitz; Raphaël Huser. "Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning". Technometrics (2024): https://doi.org/10.1080/00401706.2024.2304334.
    10.1080/00401706.2024.2304334
  12. Daniela Cisneros; Arnab Hazra; Raphaël Huser. "Spatial Wildfire Risk Modeling Using a Tree-Based Multivariate Generalized Pareto Mixture Model". Journal of Agricultural, Biological and Environmental Statistics (2024): https://doi.org/10.1007/s13253-023-00596-5.
    10.1007/s13253-023-00596-5
  13. Peng Zhong; Raphaël Huser; Thomas Opitz. "Exact Simulation of Max-Infinitely Divisible Processes". Econometrics and Statistics (2024): https://doi.org/10.1016/j.ecosta.2022.02.007.
    10.1016/j.ecosta.2022.02.007
  14. Ashok Dahal; Hakan Tanyas; Cees van Westen; Mark van der Meijde; Paul Martin Mai; Raphaël Huser; Luigi Lombardo. "Space–time landslide hazard modeling via Ensemble Neural Networks". Natural Hazards and Earth System Sciences (2024): https://doi.org/10.5194/nhess-24-823-2024.
    10.5194/nhess-24-823-2024
  15. Matthew Sainsbury-Dale; Andrew Zammit-Mangion; Raphaël Huser. "Likelihood-Free Parameter Estimation with Neural Bayes Estimators". The American Statistician (2024): https://doi.org/10.1080/00031305.2023.2249522.
    10.1080/00031305.2023.2249522
  16. "A neural network-based adaptive cut-off approach to normality testing for dependent data". Statistics and Computing (2024): http://hdl.handle.net/10754/702120.
    10.1007/s11222-024-10551-0
  17. "Neural Methods for Amortized Inference". Annual Review of Statistics and Its Application (2024): http://hdl.handle.net/10754/701225.
    10.1146/annurev-statistics-112723-034123
  18. "Max-convolution processes with random shape indicator kernels". Journal of Multivariate Analysis (2024): http://hdl.handle.net/10754/698924.
    10.1016/j.jmva.2024.105340
  19. "Neural Bayes estimators for censored inference with peaks-over-threshold models". (2024): http://hdl.handle.net/10754/702558.
  20. Rishikesh Yadav; Raphaël Huser; Thomas Opitz; Luigi Lombardo. "Joint modelling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions". Journal of the Royal Statistical Society Series C: Applied Statistics (2023): https://doi.org/10.1093/jrsssc/qlad077.
    10.1093/jrsssc/qlad077
  21. Mahnoor Ahmed; Hakan Tanyas; Raphaël Huser; Ashok Dahal; Giacomo Titti; Lisa Borgatti; Mirko Francioni; Luigi Lombardo. "Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system". International Journal of Applied Earth Observation and Geoinformation (2023): https://doi.org/10.1016/j.jag.2023.103593.
    10.1016/j.jag.2023.103593
  22. Zhongwei Zhang; Reinaldo B. Arellano-Valle; Marc G. Genton; Raphaël Huser. "Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data". Biometrics (2023): https://doi.org/10.1111/biom.13731.
    10.1111/biom.13731
  23. Zhongwei Zhang; Elias Krainski; Peng Zhong; Harvard Rue; Raphaël Huser. "Joint modeling and prediction of massive spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach". Extremes (2023): https://doi.org/10.1007/s10687-023-00463-z.
    10.1007/s10687-023-00463-z
  24. Miguel de Carvalho; Raphael Huser; Rodrigo Rubio. "Similarity-based clustering for patterns of extreme values". Stat (2023): https://doi.org/10.1002/sta4.560.
    10.1002/sta4.560
  25. Yan Gong; Raphaël Huser. "Flexible modeling of multivariate spatial extremes". Spatial Statistics (2022): https://doi.org/10.1016/j.spasta.2022.100713.
    10.1016/j.spasta.2022.100713
  26. Rishikesh Yadav; Raphaël Huser; Thomas Opitz. "A flexible Bayesian hierarchical modeling framework for spatially dependent peaks-over-threshold data". Spatial Statistics (2022): https://doi.org/10.1016/j.spasta.2022.100672.
    10.1016/j.spasta.2022.100672
  27. Daniela Castro-Camilo; Raphaël Huser; Håvard Rue. "Practical strategies for generalized extreme value-based regression models for extremes". Environmetrics (2022): https://doi.org/10.1002/env.2742.
    10.1002/env.2742
  28. Zhongwei Zhang; Raphaël Huser; Thomas Opitz; Jennifer Wadsworth. "Modeling spatial extremes using normal mean-variance mixtures". Extremes (2022): https://doi.org/10.1007/s10687-021-00434-2.
    10.1007/s10687-021-00434-2
  29. Raphaël Huser; Jennifer L. Wadsworth. "Cover Image". WIREs Computational Statistics (2022): https://doi.org/10.1002/wics.1577.
    10.1002/wics.1577
  30. "A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes". Accepted by Extremes (2022): http://hdl.handle.net/10754/688062.
  31. "Practical strategies for GEV-based regression models for extremes". Environmetrics (2022): http://hdl.handle.net/10754/669796.
  32. Luigi Lombardo; Hakan Tanyas; Raphaël Huser; Fausto Guzzetti; Daniela Castro-Camilo. "Landslide size matters: A new data-driven, spatial prototype". Engineering Geology 293 (2021): 106288-106288. https://doi.org/10.1016/j.enggeo.2021.106288.
    10.1016/j.enggeo.2021.106288
  33. "Effects of fuel composition variability on high temperature combustion properties: A statistical analysis". (2020):
    10.1016/j.jaecs.2020.100012
  34. "Advances in statistical modeling of spatial extremes". (2020):
    10.1002/wics.1537
  35. "Spatial hierarchical modeling of threshold exceedances using rate mixtures". (2020):
    10.1002/env.2662
  36. "Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model". (2020):
  37. "Space-time landslide predictive modelling". (2020):
    10.1016/j.earscirev.2020.103318
  38. "Max-infinitely divisible models and inference for spatial extremes". (2020):
    10.1111/sjos.12491
  39. "Discussion of "Graphical models for extremes" by Sebastian Engelke and Adrien S. Hitz". (2020):
    10.1111/rssb.12355
  40. "Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models". (2020):
    10.1214/20-BA1219
  41. "A hierarchical max-infinitely divisible spatial model for extreme precipitation". (2020):
    10.1080/01621459.2020.1750414
  42. "Proteome-level assessment of origin, prevalence and function of leucine-aspartic acid (LD) motifs". Bioinformatics (2020): http://dx.doi.org/10.1093/bioinformatics/btz703.
    10.1093/bioinformatics/btz703
  43. "Editorial: EVA 2019 data competition on spatio-temporal prediction of Red Sea surface temperature extremes". Extremes (2020): http://dx.doi.org/10.1007/s10687-019-00369-9.
    10.1007/s10687-019-00369-9
  44. "Local likelihood estimation of complex tail dependence structures, applied to U.S. precipitation extremes". Journal of the American Statistical Association (2019): http://dx.doi.org/10.1080/01621459.2019.1647842.
    10.1080/01621459.2019.1647842
  45. "Bayesian modeling of air pollution extremes using nested multivariate max-stable processes". Biometrics (2019): http://dx.doi.org/10.1111/biom.13051.
    10.1111/biom.13051
  46. "A spliced gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting". Journal of Agricultural, Biological and Environmental Statistics (2019): http://dx.doi.org/10.1007/s13253-019-00369-z.
    10.1007/s13253-019-00369-z
  47. "Bayesian model averaging over tree-based dependence structures for multivariate extremes". Journal of Computational and Graphical Statistics (2019): http://dx.doi.org/10.1080/10618600.2019.1647847.
    10.1080/10618600.2019.1647847
  48. "Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides". Journal of Geophysical Research: Earth Surface (2019): http://dx.doi.org/10.1029/2019jf005056.
    10.1029/2019jf005056
  49. "Discussion on the meeting on ‘Data visualization’". Journal of the Royal Statistical Society: Series A (Statistics in Society) (2019): http://dx.doi.org/10.1111/rssa.12435.
    10.1111/rssa.12435
  50. "Modeling spatial processes with unknown extremal dependence class". Journal of the American Statistical Association (2019): http://dx.doi.org/10.1080/01621459.2017.1411813.
    10.1080/01621459.2017.1411813
  51. "Full likelihood inference for max-stable data". Stat (2019): http://dx.doi.org/10.1002/sta4.218.
    10.1002/sta4.218
  52. "INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles". Extremes (2018): http://dx.doi.org/10.1007/s10687-018-0324-x.
    10.1007/s10687-018-0324-x
  53. "Discussion of "Using stacking to average Bayesian predictive distributions" by Yao et al.". Bayesian Analysis (2018): http://dx.doi.org/10.1214/17-ba1091.
    10.1214/17-ba1091
  54. "Hierarchical archimax copulas". Journal of Multivariate Analysis (2018): http://dx.doi.org/10.1016/j.jmva.2018.05.001.
    10.1016/j.jmva.2018.05.001
  55. "Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster". Stochastic Environmental Research and Risk Assessment (2018): http://dx.doi.org/10.1007/s00477-018-1518-0.
    10.1007/s00477-018-1518-0
  56. "Modeling soil organic carbon with quantile regression: Dissecting predictors' effects on carbon stocks". Geoderma (2018): http://dx.doi.org/10.1016/j.geoderma.2017.12.011.
    10.1016/j.geoderma.2017.12.011
  57. "A comparison of dependence function estimators in multivariate extremes". Statistics and Computing (2018): http://dx.doi.org/10.1007/s11222-017-9745-7.
    10.1007/s11222-017-9745-7
  58. "Factor copula models for replicated spatial data". Journal of the American Statistical Association (2018): http://dx.doi.org/10.1080/01621459.2016.1261712.
    10.1080/01621459.2016.1261712
  59. "Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model". Environmental Modelling & Software (2017): http://dx.doi.org/10.1016/j.envsoft.2017.08.003.
    10.1016/j.envsoft.2017.08.003
  60. "Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures". Spatial Statistics (2017): http://dx.doi.org/10.1016/j.spasta.2017.06.004.
    10.1016/j.spasta.2017.06.004
  61. "High-order composite likelihood inference for max-stable distributions and processes". Journal of Computational and Graphical Statistics (2016): http://dx.doi.org/10.1080/10618600.2015.1086656.
    10.1080/10618600.2015.1086656
  62. "Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression". IEEE Transactions on Smart Grid (2016): http://dx.doi.org/10.1109/tsg.2016.2527820.
    10.1109/tsg.2016.2527820
  63. "Non-stationary dependence structures for spatial extremes". Journal of Agricultural, Biological, and Environmental Statistics (2016): http://dx.doi.org/10.1007/s13253-016-0247-4.
    10.1007/s13253-016-0247-4
  64. "Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection". Water Resources Research (2016): http://dx.doi.org/10.1002/2015wr018552.
    10.1002/2015wr018552
  65. "Likelihood estimators for multivariate extremes". Extremes (2016): http://dx.doi.org/10.1007/s10687-015-0230-4.
    10.1007/s10687-015-0230-4
  66. "Statistics of extremes". Annual Review of Statistics and Its Application (2015): http://dx.doi.org/10.1146/annurev-statistics-010814-020133.
    10.1146/annurev-statistics-010814-020133
  67. "Visuanimation in statistics". Stat (2015): http://dx.doi.org/10.1002/sta4.77.
    10.1002/sta4.77
  68. "Space-time modelling of extreme events". Journal of the Royal Statistical Society: Series B (Statistical Methodology) (2014): http://dx.doi.org/10.1111/rssb.12035.
    10.1111/rssb.12035
  69. "Nonstationary positive definite tapering on the plane". Journal of Computational and Graphical Statistics (2013): http://dx.doi.org/10.1080/10618600.2012.729982.
    10.1080/10618600.2012.729982
  70. "Geostatistics of dependent and asymptotically independent extremes". Mathematical Geosciences (2013): http://dx.doi.org/10.1007/s11004-013-9469-y.
    10.1007/s11004-013-9469-y
  71. "Composite likelihood estimation for the Brown-Resnick process". Biometrika (2013): http://dx.doi.org/10.1093/biomet/ass089.
    10.1093/biomet/ass089
Capítulo de livro
  1. "Bayesian Latent Gaussian Models for High-Dimensional Spatial Extremes". 2023.
    10.1007/978-3-031-39791-2_7
Documento de trabalho
  1. 2024. "The Efficient Tail Hypothesis: An Extreme Value Perspective on Market Efficiency". http://hdl.handle.net/10754/700006.
  2. 2024. "Statistics of Extremes for Neuroscience". http://hdl.handle.net/10754/698042.
  3. 2023. "Deep graphical regression for jointly moderate and extreme Australian wildfires". http://hdl.handle.net/10754/693898.
  4. 2023. "Extremal Dependence of Moving Average Processes Driven by Exponential-Tailed Lévy Noise". http://hdl.handle.net/10754/693391.
  5. 2023. "Flexible and efficient spatial extremes emulation via variational autoencoders". http://hdl.handle.net/10754/693139.
  6. 2023. "Likelihood-free neural Bayes estimators for censored inference with peaks-over-threshold models". http://hdl.handle.net/10754/693052.
  7. 2023. "Measuring Information Transfer Between Nodes in a Brain Network through Spectral Transfer Entropy". http://hdl.handle.net/10754/690353.
  8. 2022. "Joint Modeling and Prediction of Massive Spatio-Temporal Wildfire Count and Burnt Area Data with the INLA-SPDE Approach". http://hdl.handle.net/10754/675560.
  9. 2022. "Spatial modeling and future projection of extreme precipitation extents". http://hdl.handle.net/10754/686583.
  10. 2022. "Flexible Modeling of Nonstationary Extremal Dependence Using Spatially-Fused LASSO and Ridge Penalties". http://hdl.handle.net/10754/688051.
  11. 2022. "Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning". http://hdl.handle.net/10754/688049.
  12. 2022. "Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning". http://hdl.handle.net/10754/688050.
  13. 2022. "Fast Optimal Estimation with Intractable Models using Permutation-Invariant Neural Networks". http://hdl.handle.net/10754/680933.
  14. 2022. "Vecchia Likelihood Approximation for Accurate and Fast Inference in Intractable Spatial Extremes Models". http://hdl.handle.net/10754/688058.
  15. 2022. "Similarity-based clustering for patterns of extreme values". http://hdl.handle.net/10754/688059.
  16. 2022. "An Efficient Workflow for Modelling High-Dimensional Spatial Extremes". http://hdl.handle.net/10754/688052.
  17. 2022. "A unifying partially-interpretable framework for neural network-based extreme quantile regression". http://hdl.handle.net/10754/680462.
  18. 2022. "Club Exco: clustering brain extreme communities from multi-channel EEG data". http://hdl.handle.net/10754/686603.
  19. 2022. "Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals". http://hdl.handle.net/10754/680112.
  20. 2022. "Patterns in Spatio-Temporal Extremes". http://hdl.handle.net/10754/686641.
  21. 2021. "Exact Simulation of Max-Infinitely Divisible Processes". http://hdl.handle.net/10754/668027.
  22. 2021. "Modeling Spatial Data with Cauchy Convolution Processes". http://hdl.handle.net/10754/667610.
  23. 2021. "Modeling spatial extremes using normal mean-variance mixtures". http://hdl.handle.net/10754/669326.
Poster em conferência
  1. "Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster.". 2018.
Pré-impressão
  1. Mahnoor Ahmed; Hakan Tanyas; Raphaël Huser; Ashok Dahal; Giacomo Titti; Lisa Borgatti; Mirko Francioni; Luigi Lombardo. "Dynamic rainfall-induced landslide susceptibility: a step towards a unified forecasting system". 2023. https://doi.org/10.31223/X5JT2D.
    10.31223/X5JT2D
  2. Ashok Dahal; Hakan Tanyas; Cees Van Westen; Mark Van der Meijde; Paul Martin Mai; Raphael Huser; Luigi Lombardo. "Space-time modelling of co-seismic and post-seismic landslide hazard via Ensemble Neural Networks.". 2023. https://doi.org/10.5194/egusphere-egu23-3496.
    10.5194/egusphere-egu23-3496
  3. Ashok Dahal; David Alejandro Casto Cruz; Hakan Tanyas; Islam Fadel; Paul Martin Mai; Mark van der Meijde; Cees van Westen; Raphaël Huser; Luigi Lombardo. "From ground motion simulations to landslide occurrence prediction". 2023. https://doi.org/10.31223/X5WM0P.
    10.31223/X5WM0P
  4. Jordan Richards; Raphaël Huser. "Insights into the drivers and spatio-temporal trends of extreme wildfires with statistical deep-learning". 2023. https://doi.org/10.5194/egusphere-egu23-2332.
    10.5194/egusphere-egu23-2332
  5. Zhongwei Zhang; Raphaël Huser; Thomas Opitz; Jennifer Wadsworth. "Modeling Spatial Extremes Using Normal Mean-Variance Mixtures". 2022. https://doi.org/10.5194/egusphere-egu22-4136.
    10.5194/egusphere-egu22-4136
  6. Jordan Richards; Raphaël Huser; Emanuele Bevacqua; Jakob Zscheischler. "Partially interpretable neural networks for high-dimensional extreme quantile regression: With application to wildfires within the Mediterranean Basin". 2022. https://doi.org/10.5194/egusphere-egu22-2179.
    10.5194/egusphere-egu22-2179
  7. Raphael Huser; Arnab Hazra; David Bolin. "Realistic and Fast Modeling of Spatial Extremes over Large Geographical Domains". 2022. https://doi.org/10.5194/egusphere-egu22-6595.
    10.5194/egusphere-egu22-6595
  8. Ashok Dahal; Hakan Tanyas; Cees van Westen; Mark van der Meijde; Paul Martin Mai; Raphaël Huser; Luigi Lombardo. "Space-time landslide hazard modeling via Ensemble Neural Networks". 2022. https://doi.org/10.31223/X5B075.
    10.31223/X5B075
  9. "Tractable Bayes of skew-elliptical link models for correlated binary data". 2021.
  10. "Landslide size matters: a new spatial predictive paradigm". 2021.
    10.5194/egusphere-egu21-2443
  11. "Conex-Connect: Learning patterns in extremal brain connectivity from multi-channel EEG data". 2021.
  12. "High-resolution Bayesian mapping of landslide hazard with unobserved trigger event". 2020.
  13. "Modeling non-stationary temperature maxima based on extremal dependence changing with event magnitude". 2020.
  14. "Approximate Bayesian inference for spatio-temporal flood frequency analysis". 2020.
  15. "Asymmetric tail dependence modeling, with application to cryptocurrency market data". 2019.
Tese / Dissertação
  1. "Statistical Modeling and Inference for Spatio-Temporal Extremes". 2013. http://infoscience.epfl.ch/record/188557.
    10.5075/EPFL-THESIS-5946

Outros

Outra produção
  1. Statistical Modeling of Non-Stationary Heatwave Hazard. 2021. Peng Zhong; Raphael Huser; Thomas Opitz. https://doi.org/10.5194/egusphere-egu21-56.
    10.5194/egusphere-egu21-56
Software
  1. "siliusmv/spatialConditionalExtremes:". 2022.
  2. "Jbrich95/pinnEV: Partially-Interpretable Neural Networks for Extreme Value modelling". 2022.
  3. "PangChung/SpatialScalePrecipExtremes:". 2022.
  4. "matheusguerrero/club-exco: Toy example for Club Exco method.". 2022.
Atividades

Orientação

Título / Tema
Papel desempenhado 		Curso (Tipo)
Instituição / Organização
2023/09/01 - Atual TBD
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2022/01/01 - Atual Modeling of nonstationary extremal dependence
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2021/01/01 - Atual TBD
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2020/09/01 - Atual Modeling multivariate low and large extremes without threshold selections
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2017/09/01 - 2023/09/15 Extreme-value models and graphical methods for spatial wildfire risk assessment
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2018/01/01 - 2023/02/15 Flexible multivariate, spatial, and causal models for extremes
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2018/09/01 - 2022/09/15 Flexible extremal dependence models for multivariate and spatial extremes
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2019/01/01 - 2022/04/15 Modeling and simulation of spatial extremes based on max-infinitely divisible and related processes
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2018/09/01 - 2022/04/15 Modeling and inference for multivariate time series, with applications to integer-valued processes and nonstationary extreme data
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2017/09/01 - 2022/04/15 Bayesian modeling of sub-asymptotic spatial extremes
Orientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita
2014/09/01 - 2017/12/01 Models and inference for multivariate spatial extremes
Coorientador
 Statistics (Doutoramento)
King Abdullah University of Science and Technology, Arábia Saudita

Arbitragem científica em revista

Nome da revista (ISSN) Editora
2022 - Atual Journal of the Royal Statistical Society: Series C
2022 - Atual Statistics and Computing
2020 - Atual Environmetrics
2019 - Atual Journal of Agricultural, Biological and Environmental Statistics
2017 - Atual Extremes
2020 - 2021 Journal of the Korean Statistical Society
2019 - 2021 Econometrics and Statistics

Tutoria

Tópico Nome do aluno
2025/01/01 - Atual Postdoc supervision Simon Nik
2024/10/01 - Atual Postdoc supervision Matthew Sainsbury-Dale
2024/08/01 - Atual Postdoc supervision Bingqing Yi
2021/11/01 - 2024/01/01 Postdoc supervision Jordan Richards
2018/03/01 - 2021/12/01 Postdoc supervision Arnab Hazra
2015/11/01 - 2019/06/01 Postdoc supervision Daniela Castro-Camilo
2016/04/01 - 2018/12/01 Postdoc supervision Luigi Lombardo
Distinções

Prémio

2022 Abdel El-Shaarawi Early Investigator Award
The International Environmetrics Society, Estados Unidos
2019 ENVR Early Investigator Award
American Statistical Association, Estados Unidos
2018 Best 2016 paper published in the Journal of Agricultural, Biological and Environmental Statistics
2015 Lambert Award
Swiss Statistical Society, Suiça
2014 EPFL Doctorate Award
École Polytechnique Fédérale de Lausanne, Suiça

Outra distinção

2016 Elected member of the International Statistical Institute
International Statistical Institute, Países Baixos