Recognizing and retaining AI excellence: Five UAlberta researchers named CIFAR AI Chairs

Five researchers in the Faculty of Science's Department of Computing Science have been named Canada CIFAR AI Chairs at AICan 2019, joining a rapidly growing community of world-leading researchers in Canada, Alberta, and Edmonton.

The prestigious Canada CIFAR AI Chairs program, funded by the Government of Canada with $86.5 million over five years, provides researchers with long-term, dedicated research funding to support their research programs and help them to train the next generation of AI leaders. The program is part of the $125 million Pan-Canadian AI Strategy, which was launched in March 2017 and recognized Edmonton for its strengths in artificial intelligence and machine learning.

Five of the 34 Canada-wide appointments recognized the AI talent in the University of Alberta's Faculty of Science-who are also research fellows at the Alberta Machine Intelligence Institute (Amii).

Meet the five UAlberta scientists appointed as CIFAR AI Chairs and learn more about their research:

Rupam Mahmood

Rupam Mahmood, a University of Alberta alumnus, joined the Department of Computing Science as an assistant professor in 2019 specializing in reinforcement learning. His research goal is to develop AI mechanisms for continually improving robot minds.

Mahmood is also an Amii fellow and director of the Reinforcement Learning and Artificial Intelligence (RLAI) lab, and is making use of a robotic arm donated by industry partners at Kindred AI in the classroom to teach students about reinforcement learning. During his doctoral studies, he was advised by Richard Sutton, professor in the Department of Computing Science, Distinguished Research Scientist at DeepMind, and Amii fellow-widely regarded as the pioneer of reinforcement learning.

Learn more about Mahmood's work in reinforcement learning.

Lili Mou

Lili Mou is one of five UAlberta researchers named 2019 CIFAR AI chairs. Photo credit: John Ulan

Imagine if a program were able to summarize a longform article into a few sentences. Or pick up on the sentiment of a text message. Lili Mou's work with deep learning applied to natural language processing pushes towards this future.

Mou, assistant professor in the Department of Computing Science and Amii fellow, is also the inaugural AltaML Professor in Natural Language Processing. His work's ultimate goal is building intelligent systems capable of understanding and interacting with humans using both text understanding and text generation.

Learn more about Mou's research program in natural language processing.

Csaba Szepesvári

Csaba Szepesvári advances research by designing smarter, more effective learning algorithms. A professor in the Department of Computing Science and Amii fellow, his work builds on other research by indicating strengths, weaknesses and possibilities of existing algorithms.

This is well exemplified by Szepesvári's work on the Upper Confidence bounds applied to Trees (UCT) algorithm-which he co-developed and which addressed a flaw in previous iterations of the Monte Carlo tree search. The UCT algorithm has been applied widely since and is at the heart of many recent advancements in games research, including in AlphaGo, the first computer Go program capable of professional-level play.

Nathan Sturtevant

Nathan Sturtevant is one of five UAlberta researchers named 2019 CIFAR AI chairs. Photo credit: John Ulan

Nathan Sturtevant, professor in the Department of Computing Science and Amii fellow, runs the MovingAI lab-where his work focuses on artificial intelligence research to improve pathfinding-the way programs figure out how to move around three-dimensional space.

Sturtevant has also spent time improving algorithms from decades-old areas of search, such as bidirectional search and suboptimal search.

"We've achieved milestone results over the last couple of years, introducing new algorithms which are fundamental breakthroughs in our understanding of search," said Sturtevant, who is also on the leading edge of the field. He is currently working on using machine learning to summarize incredibly large datasets with enough detail that one can still apply search algorithms to the dataset and get quality results.

Sturtevant's work in pathfinding also has applications in video games, and he has recently begun a new research partnership with the Edmonton-based office of the international company Improbable, an exciting-and widely accessible-application of their cutting-edge work.

Learn more about Sturtevant's work in artificial intelligence and pathfinding.

Adam White

Adam White is a UAlberta alumnus, new assistant professor, and 2019 CIFAR AI Chair. Photo

Can intelligent systems develop common-sense knowledge about the world around it? University of Alberta alumnus Adam White's research explores this question. As an assistant professor in the Department of Computing Science and Amii fellow, his research focuses on systems which learn through self-supervised, trial-and-error interaction.

"Children learn how their limbs work, how to manipulate objects, and all kinds of simple facts about the world by simply trying things and observing the outcomes," explained White. "I want to build simulated and robotic learning systems that learn for weeks and months-similar to human babies and animals-coming to understand the world, and building on previous learning to understand more complex things and achieve goals."

Learn more about White and his research in artificial intelligence.

Interested in learning more about reinforcement learning? Hear more from White as one of the instructors of the UAlberta online course, the Reinforcement Learning Specialization.

Congratulations to all of the newly-appointed CIFAR AI Chairs! Mahmood, Mou, Sturtevant, Szepesvári, and White join 2018 CIFAR chairs in the Faculty of Science Alona Fyshe, Martha White, and James Wright.