
Dale Schuurmans
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Fellow & Canada CIFAR AI Chair
Academic Affiliations
Industry and Research Affiliations
Areas of Expertise
Dale Schuurmans’ long term research goal is to develop systems that learn predictive models from massive data sources when the requisite models are complex
Dale Schuurmans’ long term research goal is to develop systems that learn predictive models from massive data sources when the requisite models are complex – for example: in perception, language interpretation, information extraction, bioinformatics, or robot learning. Some of the key challenges he tackles are knowledge representation for learning -- how to usefully express and debug prior domain assumptions -- and navigating complex model spaces -- how to find good models while avoiding over/under-fitting. Some of Dale’s ongoing projects include statistical natural language modelling, reinforcement learning, and learning search control. He has also developed new methods for probabilistic inference, optimization, and constraint satisfaction. He has worked in many areas of machine learning and artificial intelligence, including model selection, on-line learning, adversarial optimization, boolean satisfiability, sequential decision making, reinforcement learning, Bayesian optimization, semi-definite methods for unsupervised learning, dimensionality reduction, and robust estimation.
Dale is a Professor in the Department of Computing Science at the University of Alberta and a Senior Staff Research Scientist at Google Brain in Edmonton, Canada. He is the Associate Editor in Chief of the IEEE Transactions on Pattern Analysis and Machine Intelligence and sits on the Advisory Board for the Neural Information Processing Systems (NeurIPS) conference. Dale is also a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and has received best paper awards at top-tier conferences such as NeurIPS, the IEEE International Conference on Automation and Logistics and at the International Conference on Machine Learning (ICML). Dale has co-authored more than 300 papers, published in venues such as the International Joint Conference on Artificial Intelligence (IJCAI), AAAI, ICML, and ICAL. Dale has supervised more than 50 early-career researchers at the M.Sc and Ph.D. levels.
Dale has received best paper awards at top-tier conferences such as NeurIPS, the IEEE International Conference on Automation and Logistics and at the International Conference on Machine Learning.
Feb 11th 2021
Research Post
Feb 1st 2021
Research Post
Jan 19th 2021
News
As part of the January 2021 AICan, Amii is pleased to welcome 15 new Canada CIFAR AI Chairs into our research community.
Looking to build AI capacity? Need a speaker at your event?