About Daniela Cisneros Daniela Cisneros Ph.D. Student, Statistics Statistics of extremes spatio-temporal statistics Daniela Cisneros was a Ph.D. student in Statistics at the King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Raphaël Huser. Daniela successfully defended her PhD thesis entitled " Extreme-Value Models and Graphical Methods for Spatial Wildfire Risk Assessment" on September 11th, 2023; see her PhD thesis here. Her PhD committee was composed of Professors Raphaël Huser (chair), Jorge Mateu (external examiner from Universitat Jaume I, Castillón, Spain), Hernando Ombao, and Matteo Parsani. For her next career steps, Daniela will return to Mexico where Events Presented Events Sep 10 - Sep 16, 2023 Spatial Models and Extreme-Value Methods for Wildfire Risk Assessment Daniela Cisneros, Ph.D. Student, Statistics Sep 11, 16:00 - 17:00 B3 L5 R5220 extreme statistics Applied Machine Learning geospatial statistics The statistical modeling of spatial and extreme events provides a framework for the development of techniques and models to describe natural phenomena in a variety of environmental, geoscience, and climate science applications. In a changing climate, various natural hazards, such as wildfires, are believed to have evolved in frequency, size, and spatial extent, although regional responses may vary.
Spatial Models and Extreme-Value Methods for Wildfire Risk Assessment Daniela Cisneros, Ph.D. Student, Statistics Sep 11, 16:00 - 17:00 B3 L5 R5220 extreme statistics Applied Machine Learning geospatial statistics The statistical modeling of spatial and extreme events provides a framework for the development of techniques and models to describe natural phenomena in a variety of environmental, geoscience, and climate science applications. In a changing climate, various natural hazards, such as wildfires, are believed to have evolved in frequency, size, and spatial extent, although regional responses may vary.
