About Rishikesh Yadav Rishikesh Yadav Ph.D. Student, Statistics spatial statistics extreme-value theory spatio-temporal statistics bayesian inference Rishikesh Yadav was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Rishikesh successfully defended his PhD thesis entitled " Bayesian Modeling of Sub-Asymptotic Spatial Extremes" on April 5th, 2022; see his PhD thesis here. His PhD committee was composed of Professors Raphaël Huser (chair), Philippe Naveau (external examiner from CNRS, France), Marc Genton, and Ajay Jasra. For his next career steps, Rishikesh has accepted a postdoctoral position at HEC Montréal, Canada, under the joint supervision Articles Related News August 2023 New paper accepted in Journal of the Royal Statistical Society: Series C 1 min read · Sat, Aug 5 2023 Spotlight News New paper accepted: Yadav, R., Huser, R., Opitz, T., and Lombardo, L. (2023+), Joint modeling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions, Journal of the Royal Statistical Society: Series C, to appear [ PDF preprint]. January 2023 Two new papers in Extremes 1 min read · Thu, Jan 19 2023 Spotlight News Two new papers accepted to the Extremes Special Issue on the EVA Data Competition: Zhang, Z., Krainski, E., Zhong, P., Rue, H., and Huser, R. (2023+), Joint modeling and prediction of massive Spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach, Extremes, to appear [ PDF preprint]. Cisneros, D., Gong, Y., Yadav, R., Hazra, A., and Huser, R. (2022+), A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes, Extremes, to appear [ PDF preprint]. May 2022 A flexible Bayesian hierarchical modeling framework for spatially dependent peaks-over-threshold data 1 min read · Wed, May 11 2022 News Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication. April 2022 Congratulations to Rishikesh for successfully defending his PhD thesis 1 min read · Tue, Apr 5 2022 Spotlight News Left: Rishikesh before starting his PhD defense. Right: picture taken at a group dinner with Rishikesh (center) and Prof. Raphael Huser (carrying a child next to Rishikesh) October 2020 New paper accepted in Environmetrics 2020 1 min read · Wed, Oct 21 2020 Spotlight News Statistics of extremes New paper accepted: Yadav, R., Huser, R. , and Opitz, T. (2020+), Spatial hierarchical modeling of threshold exceedances using rate mixtures , Environmetrics, to appear [ PDF preprint ].
New paper accepted in Journal of the Royal Statistical Society: Series C 1 min read · Sat, Aug 5 2023 Spotlight News New paper accepted: Yadav, R., Huser, R., Opitz, T., and Lombardo, L. (2023+), Joint modeling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions, Journal of the Royal Statistical Society: Series C, to appear [ PDF preprint].
Two new papers in Extremes 1 min read · Thu, Jan 19 2023 Spotlight News Two new papers accepted to the Extremes Special Issue on the EVA Data Competition: Zhang, Z., Krainski, E., Zhong, P., Rue, H., and Huser, R. (2023+), Joint modeling and prediction of massive Spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach, Extremes, to appear [ PDF preprint]. Cisneros, D., Gong, Y., Yadav, R., Hazra, A., and Huser, R. (2022+), A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes, Extremes, to appear [ PDF preprint].
A flexible Bayesian hierarchical modeling framework for spatially dependent peaks-over-threshold data 1 min read · Wed, May 11 2022 News Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication.
Congratulations to Rishikesh for successfully defending his PhD thesis 1 min read · Tue, Apr 5 2022 Spotlight News Left: Rishikesh before starting his PhD defense. Right: picture taken at a group dinner with Rishikesh (center) and Prof. Raphael Huser (carrying a child next to Rishikesh)
New paper accepted in Environmetrics 2020 1 min read · Wed, Oct 21 2020 Spotlight News Statistics of extremes New paper accepted: Yadav, R., Huser, R. , and Opitz, T. (2020+), Spatial hierarchical modeling of threshold exceedances using rate mixtures , Environmetrics, to appear [ PDF preprint ].
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