BiographyGodfried T. Toussaint is a Canadian computer scientist born in Belgium. Presently, he is a Research Professor of Computer Science at the University of New York, Abu Dhabi, United Arab Emirates, a Research Affiliate at the Massachusetts Institute of Technology in the Computer Science and Artificial Intelligence Laboratory, a Researcher in the Center for Interdisciplinary Research in Music Media and Technology (CIRMMT) in the Schulich School of Music at McGill University, and an Emeritus Professor of Computer Science at McGill. After receiving a PhD in electrical engineering from the University of British Columbia in Vancouver, Canada, he taught and did research at the School of Computer Science at McGill University, in the areas of information theory, pattern recognition, pattern analysis and design, computational geometry, instance-based learning, music information retrieval, and computational music theory. In 1978, he received the Pattern Recognition Society’s Best Paper of the Year Award and in 1985 he was awarded a Senior Killam Research Fellowship by the Canada Council. In May 2001, he was awarded the David Thomson Award for excellence in graduate supervision and teaching at McGill University. He is a founder and cofounder of several international conferences and workshops on computational geometry. He is an editor of several journals, has appeared on television programs to explain his research on the mathematical analysis of flamenco rhythms, and has published more than 360 papers. In 2009, he was awarded a Radcliffe Fellowship by the Radcliffe Institute for Advanced Study at Harvard University, for the 2009–2010 academic year, to carry out a research project on the phylogenetic analysis of the musical rhythms of the world. After spending an additional year at Harvard University, in the music department, he moved in August 2011 to New
York University in Abu Dhabi.
Ph.D., University of British Columbia, Vancouver, Canada.
Areas of Research / Professional Expertise
Discrete and Computational Geometry, Computational Music Theory, Music Information Retrieval, Machine Learning.
Science, Arts, Music, Percussion, African Drumming, History of Technology, SCUBA Diving, Travelling