Research Scientist
Research Scientist
Current
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Dr. Ait-El-Fquih is interested in various aspects of Bayesian inference and learning for complex stochastic systems. His efforts are mainly focused on the development of new efficient methods and algorithms for filtering and smoothing standard (hidden Markov) state-space dynamical models, and their extensions to more general models such as pairwise and triplet Markov models. His research also extends to (static) inverse problems for which he investigates the approximation of posterior distribution using stochastic sampling and deterministic optimization strategies. He is also interested in the application of the methods to real world problems related to data assimilation, including ocean and ground fluid modeling and forecasting and history matching, and to electrical engineering, including signal processing and wireless communications.
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