About
Ana Corberán Vallet is an Associate Professor in the Department of Statistics and Operations Research at the Faculty of Mathematics, Universitat de València, Spain. She is a member of the PROMEDyA research group, focusing on prediction and optimization under uncertainty using dynamic stochastic models.
Her research lies at the intersection of Bayesian statistics, time series forecasting, and epidemiological modeling. She specializes in developing and applying Bayesian stochastic models to real-world problems, particularly in public health, such as modeling the spread of respiratory syncytial virus. Her work often integrates simulation-based inference and spatial statistics for health survey data.
Her recent publications show a strong trend toward spatial and hierarchical Bayesian modeling, especially in health applications, with a focus on small area estimation and ordinal data analysis. She frequently collaborates with experts in mathematical epidemiology and biostatistics.
She earned her Ph.D. from the Universitat de València in 2009, supervised by Dr. José Domingo Bermúdez Edo and Dr. Enriqueta Vercher González. Her doctoral work centered on Bayesian multivariate exponential smoothing models.
She has published in journals such as Statistics in Medicine, Biometrical Journal, and Journal of Statistical Planning and Inference.
Ana Corberán Vallet advises students and collaborates on interdisciplinary research projects involving statistical modeling of health and biological systems. She is actively involved in research without mention of external grants or awards in the provided texts.
She is associated with the PROMEDyA research group, which works on dynamic stochastic models for prediction and optimization under uncertainty, particularly in health and operational contexts.
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