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Youcef Djenouri is a senior researcher at NORCE (Norwegian Research Center) from 2023. He was a research scientist at SINTEF, and a postdoc researcher at NTNU. His research interests include AI, Smart City applications, and Robotics. He published more than 150 research papers in top conferences and journals such as ICDM, ICDE, ACM KDD, IEEE TIST, IEEE TII, IEEE TCYB, and others. He is considered as one of the top 11 researchers in Norway according to Forskerforum. He is also in the list of 2% most outstanding researchers according to Stanford statistics. Dr. Youcef Djenouri recently joined the Discover AI journal (Springer), as an associate editor, and he is in the reviewer board of several journals in the field of AI such as Applied Intelligence Journal. He also organized workshops in top conferences such as ICDM, and KDD.
Lecture description: Sequence analysis aims to extract useful information from such sequence data, for example finding anomalies in traffic flow. Because sequence data occurs in any domain which involves variable dependency such as temporal measurements, their analysis is ubiquitous and very important in smart city analysis. Modern deep learning based on recurrent neural networks have been recently developed to capture the relevant features from sequence data. This talk gives an overview of existing modern recurrent neural networks for analyzing and learning from sequence data. It also shows some illustrative examples in smart city, and NLP based applications. We finish the talk by highlighting some challenges of the existing technologies for learning from sequence data.