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Scientific Advisory Board

Scientific Advisory Board

  • Masaru Kitsuregawa - University of Tokyo (Japan)
  • François Laviolette - Laval University (Canada)
  • Verena Rieser - Heriot-Watt University (UK)
  • John Shawe Taylor - University College London (UK)
  • Henri Verdier - Ambassador for Digital Affairs (France)
  • Stefan Wrobel - Université de Bonn (Germany)
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The Scientific Advisory Board assesses and directs the actions of the DATAIA Institute.
It provides guidance on the main orientations of the Institute’s scientific policy and it ensures coherence between the evolution of the activity and the scientific programs.
The committee is composed of top-level international renown scientists, who are not affiliated with any of the Institute’s  partners.
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Masaru Kitsuregawa - University of Tokyo (Japan)
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Masaru Kitsuregawa

Masaru, Kitsuregawa is Director of the National Institute of Informatics and Professor at the Institute of Industrial Science, University of Tokyo. Received Ph.D. degree from the University of Tokyo in 1983. Served in various positions such as President of Information Processing Society of Japan (2013–2015) and Chairman of Committee for Informatics, Science Council of Japan(2014-2016). He has wide research interests, especially in database engineering. He has received many awards including ACM SIGMOD E. F. Codd Innovations Award, IEICE Contribution Award, IPSJ Contribution Award, 21st Century Invention Award of National Commendation for Invention, Japan and C&C Prize. In 2013, he awarded Medal with Purple Ribbon and in 2016, the Chevalier de la Legion D’Honneur. He is a fellow of ACM, IEEE, IEICE and IPSJ.

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François Laviolette - Laval University (Canada)
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Francois Laviolette

Professor François Laviolette is the founding director of Laval University's Big Data Research Center (BDRC), which brings together more than 55 researchers from five faculties working on various fundamental and applied aspects of data science. His research focuses on artificial intelligence, especially machine learning. He is a leader in the Bayesian PAC theory, a branch of the theory of learning that provides a better understanding of existing machine learning algorithms, and also allows for the design of new ones. Professor Laviolette is interested in the development of new learning algorithms to solve new types of learning problems, including problems related to genomics and proteomics, drug discovery, and more. In this area, he has worked on interpretable artificial intelligences that can reveal new knowledge, by giving information about how decisions are made. Part of his research is to extend interpretability of AIs to other areas, such as insurance. In this regard, he owns two research chairs in interpretable machine learning, one from NSERC and the second one from CIFAR.

 

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Verena Rieser - Heriot-Watt University (UK)
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Verena Rieser

Verena Rieser is a Professor in Artificial Intelligence at Heriot-Watt University, Edinburgh, where she is affiliated with the Interaction Lab and the Edinburgh Centre for Robotics. Verena holds a PhD from Saarland University (2008) and worked as a postdoctoral researcher at the University of Edinburgh (2008-11). Her research focuses on machine learning techniques for conversational AI, i.e. spoken dialogue systems and language generation, where she has authored over 100 peer-reviewed papers and she received a number of prizes for her research. She has served the research community in a number of leadership roles, as well as scientific advisor to the government and public bodies. For the past two years, Verena and her group were the only UK team to make it through to the finals of the Amazon Alexa Prize.

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John Shawe Taylor - University College London (UK)
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John Shawe Taylor

John Shawe-Taylor is professor of Computer Science at University College London. He has helped to drive a fundamental rebirth in the field of machine learning, with applications in novel domains including computer vision, document classification, and applications in biology and medicine focussed on brain scan, immunity and proteome analysis. He has published over 250 papers and two books that have attracted over 66000 citations.

He has also been instrumental in assembling a series of influential European Networks of Excellence. The scientific coordination of these projects has influenced a generation of researchers and promoted the widespread uptake of machine learning in both science and industry that we are currently witnessing.

He was appointed UNESCO Chair of Artificial Intelligence in November 2018 and is the leading trustee of the UK Charity, Knowledge 4 All Foundation, promoting open education and helping to establish a network of AI researchers and practitioners in sub-Saharan Africa.

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Henri Verdier - Ambassador for Digital Affairs (France)
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Henri Verdier

A former student of the École Normale Supérieure, Henri Verdier was the founder and CEO of the company Odile Jacob Multimedia.

He is one of the founding members of the Cap Digital competitiveness cluster, and he served as Vice-Chairman from 2006 to 2008, before becoming Chairman of the Board of Directors from 2008 to January 2013.

Henri Verdier is also a member of the Scientific Council of the Institut Mines-Télécom, as well as a member of the ARCEP Foresight Committee and the CNIL Foresight Committee.

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Stefan Wrobel - Université de Bonn (Germany)
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Stefan Wrobel

Professor Dr. Stefan Wrobel is Professor of Computer Science at University of Bonn and Director of the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS.

He studied computer science and artificial intelligence in Bonn and Atlanta, Georgia/USA (M.S., Georgia Institute of Technology) and obtained his PhD at the University of Dortmund. After several years in research and as start-up co-founder, he was appointed professor at Magdeburg University, before taking up his current position. In addition, he is one of the directors of the Bonn-Aachen International Center for Information Technology (b-it).

Professor Wrobel’s work is focused on intelligent systems and their productive use in business applications, focusing in particular on innovations in Machine Learning, Artificial Intelligence and their foundations in big data, data ecosystems, and enterprise structures. He is the author of a large number of publications on data mining and machine learning and is on the Editorial Board of several leading academic journals in his field. He is co-speaker of ML2R, one of the German National Excellence.