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14th ICPA - Session

Session
Title: Plenary Session
Date: Tue Jun 26, 2018
Time: 8:00 AM - 9:30 AM
Moderator: Nicolas Tremblay
Defining Precision Agriculture
Nicolas Tremblay (speaker)
Research Scientist
Agriculture and Agri-Food Canada
St-Jean-sur-Richelieu, AL, Quebec J3B 3E6
CA

ISPA President from 2016 to 2018 On-Farm Experimentation Community co-lead as of October 2020

Length (approx): 30 min
 
Keynote Presentation: From Data to Decisions with Artificial Intelligence

Dr. Yoshua Bengio (computer science, 1991, McGill U; post-docs at MIT and Bell Labs) is Professor at the University of Montreal since 1993, department of computer science and operations research. He is scientific director of MILA (Montreal Institute for Learning Algorithms, currently the largest academic research group on deep learning) and IVADO (Institute for data valorization). Yoshua Bengio is Canada Research Chair in Statistical Learning Algorithms. He authored three books and over 300 publications (h-index over 100), mostly in deep learning. He holds a Canada Research Chair in Statistical Learning Algorithms, is Officer of the Order of Canada, recipient of the Marie-Victorin Quebec Prize 2017, he is a CIFAR Senior Fellow and co-directs its Learning in Machines and Brains program. He is on the NIPS foundation board (previously program chair and general chair) and co-created the ICLR conference (specialized in deep learning). He pioneered deep learning and his goal is to uncover the principles giving rise to intelligence through learning, as well as contribute to the development of AI for the benefit of all. He was just named scientist of the year in Canada for his research that revolutionized and deepened our knowledge of artificial intelligence, and his initiatives that made Montreal a hub in the sector.
 

Yoshua Bengio (speaker)
MILA
CA
Yoshua Bengio is Full Professor of the Department of Computer Science and Operations Research,head of the Montreal Institute for Learning Algorithms (MILA), CIFAR Program co-director of the CIFAR Learning in Machines and Brains program (formerly Neural Computation and Adaptive Perception), and Canada Research Chair in Statistical Learning Algorithms. His main research ambition is to understand principles of learning that yield intelligence. He teaches a graduate course in Machine Learning (IFT6266) and supervises a large group of graduate students and post-docs.His research is widely cited (over 40000 citations found by Google Scholar in June 2016, with an H-index over 80, and rising fast).
Length (approx): 50 min