Bruno Astuto Arouche Nunes | PUBTechSF@Berkeley 2019

Bruno é Data Scientist na UCSF – Department of Radiology and Biomedical Imaging. Ele apresentará seu trabalho “Modelos Deep-Learning Multi-tarefa para Estimar Automaticamente a Severidade de Lesões nas Cartilagens do Joelho com Osteoartrite” no PUBTechSF@Berkeley 2019 que acontecerá no dia 10 de outubro de 2019, a partir de 6 pm.

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Bruno is a Data Scientist with a history of working in research and industry. With more than 20 publications in conferences and top tier journals, his work has been cited more than 1600 times. He is currently acting in image and data analytics applying Deep Learning models to classification, segmentation, regression and image reconstruction problems in the Radiology department at UC San Francisco. Before joining UCSF, with a PhD in Computer Engineering from UC Santa Cruz (UCSC), and a MSc from COPPE, in the Federal University of Rio de Janeiro (UFRJ), he worked as a researcher in international research institutes, such as INRIA, in France, and also big names in the industry, such as General Electric – GE and in Brazil.

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