Dr. François Laviolette
François Laviolette received his bachelor’s degree in mathematics from Université de Montréal in 1984, his Master’s degree in 1987, and his PhD in mathematics from that same university in 1997. Right from the start the significant impact of François Laviolette’s work was felt: his PhD thesis involved solving for the first time a 60-year-old open problem in graph theory, and it was one of the finalists for the 1998 Council of Graduate Schools/University Microfilms International Distinguished Dissertation Award of Washington.
In 2002 François Laviolette joined the Department of Computer Science and Software Engineering at Université Laval as a faculty member. His research interests expanded to include supervised machine learning and more specifically PAC-Bayesian theory, the area in which he made some of his most significant contributions, regarding both the theory and the applications of machine learning. His 2016 paper simply titled “Domain-adversarial training of neural networks” is considered foundational to the area of domain-adaption learning algorithms and has been cited nearly 5,000 times. In terms of applications of AI, Professor Laviolette’s work is world-renowned in genomics, where his algorithms are used for genome-sequencing and drug discovery, and he also had a significant impact in areas such as insurance and aeronautics.
However, Professor Laviolette’s most significant impact is as a builder of the AI community. In 2015 he founded the Big Data Research Centre at Université Laval, which brings together more than 50 researchers from 6 different faculties and a diversity of research backgrounds, all working together to advance AI and data mining. He also played a significant role in the creation of the Institute Intelligence and Data, whose mission is to foster AI and data valorisation in the greater Québec City region. He was a founder of the Observatory on the Societal Impacts of AI and Digital Technologies and he contributed to the development of the Montréal Declaration for a Responsible Development of Artificial Intelligence. Likewise, when designing his research programs, Professor Laviolette consistently worked to bring together a large and diverse team of researchers. Most recently, his DEEL research program on Dependable and Explainable Learning brings together more than a dozen researchers from five Québec universities, industry partners from several companies including Thales and Bombardier, and partners from the Saint-Exupéry Institute of Technological Research in Toulouse, France. Given his amazing track-record at building communities, it’s no surprise that François Laviolette is considered a pillar of the Québec AI community.
One of François Laviolette’s final acts before passing away last December was to create a new scholarship program at Université Laval to support the next generation of AI students and future researchers, working specifically on challenges related to the development of responsible AI. His impact on the Québec AI community will live on for decades to come.
For his lifetime contribution to the field of AI, CAIAC is honoured to posthumously award Dr. François Laviolette the 2022 CAIAC Lifetime Achievement Award.