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<metaname="description" content="The NTU Graph Deep Learning Lab, headed by Dr. Xavier Bresson, investigates fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks to tackle complex data domains in physical science, natural language processing, computer vision, and combinatorial optimization.">
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<metaname="description" content="The Graph Deep Learning Lab, headed by Dr. Xavier Bresson, investigates fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks to tackle complex data domains in physical science, natural language processing, computer vision, and combinatorial optimization.">
<metaproperty="og:title" content="Xavier Bresson | NTU Graph Deep Learning Lab">
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<metaproperty="og:description" content="The NTU Graph Deep Learning Lab, headed by Dr. Xavier Bresson, investigates fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks to tackle complex data domains in physical science, natural language processing, computer vision, and combinatorial optimization."><metaproperty="og:image" content="https://graphdeeplearning.github.io/images/icon_hu027d87ac1e37f4f802995042c9999554_21044_512x512_fill_lanczos_center_2.png">
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<metaproperty="og:title" content="Xavier Bresson | Graph Deep Learning Lab">
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<metaproperty="og:description" content="The Graph Deep Learning Lab, headed by Dr. Xavier Bresson, investigates fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks to tackle complex data domains in physical science, natural language processing, computer vision, and combinatorial optimization."><metaproperty="og:image" content="https://graphdeeplearning.github.io/images/icon_hu027d87ac1e37f4f802995042c9999554_21044_512x512_fill_lanczos_center_2.png">
<p>Xavier Bresson (PhD 2005, EPFL, Switzerland) is Associate Professor in Computer Science at NTU, Singapore. He is a leading researcher in the field of Graph Deep Learning, a new framework that combines graph theory and deep learning techniques to tackle complex data domains in natural language processing, computer vision, combinatorial optimization, quantum chemistry, physics, neuroscience, genetics and social networks. In 2016, he received the highly competitive Singaporean NRF Fellowship of $2.5M to develop these deep learning techniques. He was also awarded several research grants in the U.S. and Hong Kong. As a leading researcher in the field, he has published more than 60 peer-reviewed papers in the leading journals and conference proceedings in machine learning, including articles in NeurIPS, ICML, ICLR, CVPR, JMLR. He has organized several international workshops and tutorials on AI and deep learning in collaboration with Facebook, NYU and Imperial such as the <ahref="https://bit.ly/2N65idn">2019</a> and <ahref="https://bit.ly/2TC0hug">2018 UCLA workshops</a>, the <ahref="https://bit.ly/2vJbRa0">2017 CVPR tutorial</a> and the <ahref="https://bit.ly/2YsFvOx">2017 NeurIPS tutorial</a>. He has been teaching undergraduate, graduate and industrial courses in AI and deep learning since 2014 at EPFL (Switzerland), NTU (Singapore) and <ahref="https://bit.ly/2FuDQAF">UCLA (U.S.)</a>.</p>
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<p>Xavier Bresson (PhD 2005, EPFL, Switzerland) is Associate Professor in Computer Science at NUS, Singapore. He is a leading researcher in the field of Graph Deep Learning, a new framework that combines graph theory and deep learning techniques to tackle complex data domains in natural language processing, computer vision, combinatorial optimization, quantum chemistry, physics, neuroscience, genetics and social networks. In 2016, he received the highly competitive Singaporean NRF Fellowship of $2.5M to develop these deep learning techniques. He was also awarded several research grants in the U.S. and Hong Kong. As a leading researcher in the field, he has published more than 60 peer-reviewed papers in the leading journals and conference proceedings in machine learning, including articles in NeurIPS, ICML, ICLR, CVPR, JMLR. He has organized several international workshops and tutorials on AI and deep learning in collaboration with Facebook, NYU and Imperial such as the <ahref="https://bit.ly/2N65idn">2019</a> and <ahref="https://bit.ly/2TC0hug">2018 UCLA workshops</a>, the <ahref="https://bit.ly/2vJbRa0">2017 CVPR tutorial</a> and the <ahref="https://bit.ly/2YsFvOx">2017 NeurIPS tutorial</a>. He has been teaching undergraduate, graduate and industrial courses in AI and deep learning since 2014 at EPFL (Switzerland), NTU (Singapore) and <ahref="https://bit.ly/2FuDQAF">UCLA (U.S.)</a>.</p>
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