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applications to climatic and environmental risks.
Stochastic processes: weak dependence and limit theorems.
Statistical learning: artificial neural networks
José G. Gómez-García is currently a Lecturer and Researcher (ATER) at ENSAI and the CREST lab. Before joining ENSAI, he held a similar position at AgroParisTech/INRAE/Université Paris-Saclay, where he primarily taught and researched the statistical modeling of environmental and biological data. He also completed a postdoctoral fellowship in machine learning with Jalal Fadili and Christophe Chesneau at LMNO/UNICAEN, working on mixture models and models based on deep neural networks. His academic background includes a Ph.D. in Statistics-Mathematics from CY Cergy Paris Université, under the supervision of Paul Doukhan, and a research master’s in stochastic geometry from the Central University of Venezuela, supervised by José R. León.