The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Dale Schuurmans sits on this spectrum.
This scientist: 272 publications — 68th percentile
68% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Dale Schuurmans sits on this spectrum.
This scientist: 60 D-Index — 78th percentile
78% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Dale Schuurmans is affiliated with the University of Alberta in Canada. Their primary field of study is Computer Science, with a significant focus on Artificial Intelligence, reflected by 107 publications in this subfield out of 128 total. Additional research areas include Management Science and Operations Research, Computer Vision and Pattern Recognition, Statistics and Probability, and Computer Networks and Communications.
Their research encompasses diverse topics such as Reinforcement Learning in Robotics, Topic Modeling, Natural Language Processing Techniques, Advanced Bandit Algorithms Research, Domain Adaptation and Few-Shot Learning, Stochastic Gradient Optimization Techniques, and Advanced Graph Neural Networks.
Schuurmans has contributed to numerous publications, mostly appearing in the venue arXiv (Cornell University), with 80 papers published there. Other publication venues include the Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining and the Proceedings of the AAAI Conference on Artificial Intelligence.
The scientist frequently collaborates with several co-authors, including Bo Dai, Csaba Szepesvári, Hanjun Dai, Denny Zhou, and Pieter Abbeel.
Dale Schuurmans received the distinction of Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2017 for their contributions to machine learning, including foundational methods for model selection, online learning, unsupervised learning, and sequential decision making.
Alexander J. Smola;Peter Bartlett;Bernhard Schölkopf;Dale Schuurmans
Linli Xu;James Neufeld;Bryce Larson;Dale Schuurmans
Fuchun Peng;Dale Schuurmans;Shaojun Wang
Adam J. Grove;Dale Schuurmans
Ofir Nachum;Mohammad Norouzi;Kelvin Xu;Dale Schuurmans
Ruitong Huang;Bing Xu;Dale Schuurmans;Csaba Szepesvari
Daniel Lizotte;Tao Wang;Michael Bowling;Dale Schuurmans
Yuhong Guo;Dale Schuurmans
Fuchun Peng;Dale Schuurmans
Mohamed Elgendi;Ian Norton;Matt Brearley;Derek Abbott
Alexander J. Smola;Peter Bartlett;Bernhard Schölkopf;Dale Schuurmans
Dale Schuurmans;Finnegan Southey
Fuchun Peng;Dale Schuurmans;Shaojun Wang;Vlado Keselj
Linli Xu;Dale Schuurmans
Craig Boutilier;Relu Patrascu;Pascal Poupart;Dale Schuurmans
Adam J. Grove;Nick Littlestone;Dale Schuurmans
Fuchun Peng;Dale Schuurmans;Vlado Keselj;Shaojun Wang
Linli Xu;Koby Crammer;Dale Schuurmans
Mohammad Norouzi;Samy Bengio;Zhifeng Chen;Navdeep Jaitly
T.S. Caetano;T. Caelli;D. Schuurmans;D.A.C. Barone
Ofir Nachum;Bo Dai;Ilya Kostrikov;Yinlam Chow
Rishabh Agarwal;Dale Schuurmans;Mohammad Norouzi
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