Essid

Slim Essid is Full Professor at Télécom Paris and the coordinator of the Audio Data Analysis and Signal Processing theme (ADASP). His research is on machine learning and artificial intelligence for temporal data analysis, especially multiview learning, structured prediction, representation learning and data decomposition methods. The target applications include machine listening and music content analysis (MIR); multimodal perception: human behavior analysis, affective computing, and EEG data analysis; multimedia content analysis, especially joint audiovisual data analysis.

Keywords : Multiview learning, structured prediction, representation learning, audio and multimodal data

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