*: Postdocs under my (co-)supervision

**: PhD students under my (co-)supervision

**Papers****:**

[20] Opitz, T., **Huser, R.**, Bakka, H., and Rue, H. (2018+), *INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles*, Extremes, to appear

[19] Lombardo*,
L., Opitz, T., and **Huser, R.** (2018+),
*Point process-based modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster*,
Stochastic Environmental Research and Risk Assessment, to appear

[18] **Huser, R.** and Wadsworth, J. (2018+), *Modeling spatial processes with unknown extremal dependence class*, Journal of the American Statistical Association
– Theory and Methods, to appear

[17] Hofert, M., **Huser, R.**, and Prasad, A. (2018), *Hierarchical archimax copulas*, Journal of Multivariate Analysis 167, 195-211

[16] Krupskii, P., **Huser, R.**, and Genton, M. G. (2018+), *Factor copula models for replicated spatial data*, Journal of the
American Statistical Association – Theory and Methods 113, 467-479

[15] Vettori**, S., **Huser, R.**, and Genton, M. G. (2018), *A comparison of dependence function estimators in multivariate extremes*,
Statistics and Computing 28, 525-538

[14] Lombardo*,
L., Saia, S., Schillaci, C., Mai, P. M., and **Huser, R.** (2018), *Modeling soil organic carbon with Quantile Regression: Dissecting predictors’ effects on carbon stocks*, Geoderma 318, 148-159

[13] **Huser,
R.**, Opitz, T., and Thibaud, E. (2017), *Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures*, Spatial Statistics 21, 166-186

[12] Castro
Camilo*, D., Lombardo*, L., Mai, P. M., Jie, D., and **Huser, R.** (2017), *Handling
high predictor dimensionality in slope-unit-based landslide susceptibility
models through LASSO-penalized Generalized Linear Model*, Environmental
Modelling and Software 97, 145-156

[11] Castruccio, S., **Huser, R.**, and Genton, M. G. (2016), *High-order composite likelihood inference for max-stable distributions
and processes*, Journal of Computational and Graphical Statistics 25, 1212-1229

[10] Naveau, P., **Huser, R.**, Ribereau, P., and Hannart, A. (2016), *Modeling jointly low, moderate and heavy rainfall intensities without a threshold selection*, Water Resources
Research 52, 2753-2769

[9] **Huser,
R.**, and Genton, M. G. (2016), *Non-stationary dependence structures for spatial extremes*, Journal of Agricultural,
Biological and Environmental Statistics 21, 470-491

-> Award for Best Paper published in JABES during 2016

[8] **Huser,
R.**, Davison, A. C., and Genton, M. G. (2016), *Likelihood estimators for multivariate extremes*, Extremes 19, 79-103

[7] Ben
Taieb, S., **Huser, R.**, Hyndman, R.
J., and Genton, M. G. (2016), *Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression*, IEEE Transactions on Smart Grid 7, 2448-2455

[6] Davison,
A. C., and **Huser, R.** (2015), *Statistics of Extremes*, Annual Review of
Statistics and its Application 2, 203-235

[5] Genton, M. G., Castruccio, S., Crippa, P.,
Dutta, S., **Huser, R.**, Sun, Y., and
Vettori, S. (2015), *Visuanimation in statistics*, Stat 4, 81-96

[4] **Huser,
R.**, and Davison, A. C. (2014), *Space-time modeling of extreme events*, Journal of the Royal Statistical Society –
Series B 76, 439-461

[3] Davison,
A. C., **Huser, R.** and Thibaud, E.
(2013), *Geostatistics of dependent and asymptotically independent extremes*, Mathematical Geosciences 45, 511-529

[2] **Huser,
R.**, and Davison, A. C. (2013), *Composite
likelihood estimation for the Brown-Resnick process*, Biometrika 100,
511-518

[1] Anderes, E., **Huser, R.**, Nychka, D., and Coram, M. (2013) *Nonstationary positive definite tapering on the plane*, Journal of
Computational and Graphical Statistics 22, 848-865

**Other material: Book Chapters**** and PhD Thesis:**

[3] Lombardo*, L., Opitz, T., and **Huser, R.** (2018+), *Numerical recipies for landslide spatial prediction by using R-INLA**: A step-by-step tutorial*, In *Spatial Modeling in GIS and R for Earth and Environmental Sciences*, editors H. R. Pourghasemi and C. Gokceoglu, Elsevier, Accepted

[2] Davison,
A. C., **Huser, R.**, and Thibaud, E.
(2018+), *Spatial extremes*, In *Handbook of Environmental and Ecological
Statistics*, editors A. E. Gelfand, M. Fuentes, J. A. Hoeting and R. L.
Smith, CRC Press, Accepted

[1] **Huser, R.** (2013), *Statistical Modeling and Inference for Spatio-Temporal Extremes*,
Ph.D. thesis, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne,
Switzerland

-> Lambert Award 2015 (Prize to recognize the work of young statisticians up to age 35)

-> EPFL Doctoral Award 2014 (2 laureates among 403 Ph.D. theses defended)

**Under review****:**

- Bopp, G., Shaby, B., and **Huser, R.** (2018+), *A hierarchical max-infinitely divisible process for extreme areal precipitation over watersheds*, arXiv preprint 1805.06084

- Vettori**, S., **Huser, R.**, and Genton, M. G. (2018+), *Bayesian modeling of air pollution extremes using nested multivariate max-stable processes*, arXiv preprint 1804.04588

-> *Distinguished Student Paper Award 2018, Eastern North American Region (ENAR) of the International Biometric Society*

- **Huser, R.**, Opitz, T., and Thibaud, E.
(2017+), *Penultimate modeling of spatial
extremes: statistical inference for max-infinitely divisible processes*, arXiv preprint 1801.02946

- Castro
Camilo*, D., and **Huser, R.** (2017+), *Local likelihood estimation of complex tail dependence structures in high dimensions, applied to U.S. precipitation extremes*, arXiv preprint 1710.00875

- Vettori**,
S., **Huser, R.**, Segers, J., and
Genton, M. G. (2017+), *Bayesian model
averaging over tree-based dependence structures for multivariate extremes*, arXiv preprint 1705.10488

-> ENVR Student Paper Award 2017, Section on Statistics and the Environment, ASA

- Rubio**,
R., de Carvalho, M., and **Huser, R.**
(2017+), *Similarity-based clustering for
stock market extremes*

- Dombry,
C., Genton, M. G., **Huser, R.**, and
Ribatet, M. (2017+), *Full likelihood
inference for max-stable data*, arXiv preprint 1703.08665

- Alam,
T., Alazmi, M., Naser, R., Huser, F., Momin, A. A., Walkiewicz, K. W., Canlas, C. G., **Huser, R.**, Ali, A., Merzaban, J.,
Bajic, V. B., Gao, X., and Arold, S. T. (2017+), *Proteome-level assessment of origin, prevalence and function of
Leucine-Aspartic Acid (LD) motifs*, bioRxiv preprint dio:10.1101/278903