Dr. Alexander Shvets leads the Data team at the Language Technologies Unit at the Barcelona Supercomputing Center (BSC). His main effort lies in the curation of data for the creation of foundational multilingual language models. He also contributes to the development of models and carries out research on deep learning techniques for applied tasks in text analysis.

Alexander earned his Diploma in Applied Mathematics and Computer Science from the Siberian Federal University and his Ph.D. in Computer Science from the Russian Academy of Sciences 9 years ago. Since then, he successfully worked as a lead researcher at the natural language processing group at Pompeu Fabra University (UPF), in a number of large-scale international EU-funded R&D and knowledge transfer projects, in collaboration with industrial partners (including "Social Media, Political Participation, and Accountability", beAWARE, TENSOR, V4Design, XR4Drama, MindSpaces and CONNEXIONs). His most recent projects were WELCOME and ReSilence, in the areas of multilingual conversational agents and NLP-driven design, where he led the UPF team.

His research interests are focused on deep learning approaches for text understanding including multilingual entity extraction, detection of multilingual lexical collocations, distributed dialogue assistance, aspect-oriented sentiment analysis, hate speech analysis, and text generation.

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