‘I’ve always been interested in AI because I love sci-fi books and movies, and I saw lots of friendly robots interacting with people doing nice things for them’. - Doina Precup

Doina holds a Canada Research Chair, Tier I in Machine Learning at McGill University, and co-directs the Reasoning and Learning Lab in the School of Computer Science. Doina’s research interests have an emphasis on reinforcement learning, DL, time series analysis, and various applications of these methods. Additionally, she is the Research Team Lead at DeepMind. Doina will be joining RE•WORK at the Deep Learning Summit in Montreal this October where she will be presenting her most recent work.

In 2017, Doina joined us at the first Canadian edition of RE•WORK's Deep Learning Summit having just announced the opening of the Montreal based DeepMind lab. In an episode of the Women in AI Podcast, we spoke about her journey in AI and Deep Learning as well as the landscape of AI in Montreal and Canada more generally.

In advance of Doina's presentation at this year's summit, take a look a what we learned from the podcast:

Building on the interest Doina had in sci-fi books and movies as a child, she started doing reinforcement learning in her PhD, she arrived when Rich Sutton and Andy Barto were co-teaching a class on RL based on a draft of their book. "I loved that course, it was very exciting to see these agents learning by interacting with their environments and I was hooked after that. Rich was my PhD advisor and I've been hooked ever since." Doina went on to share some of her current work splitting her time between McGill and DeepMind. As a co-director of the Reasoning and Learning Lab at McGill, she is working on building new reinforcement algorithms for learning automatically and abstractions from data, for example working on theoretical analysis of different kinds of algorithms, trying to understand their properties. Additionally, Doina shared that she also does application based work of RL, as well as other learning methods to domains that she finds compelling, such as clinical monitoring and medical image analysis, as well as analysing other types of data, like cell phone recordings. At DeepMind, however, Doina is doing mainly fundamental research in reinforcement learning and deep reinforcement learning, which we are excited to hear about in October this year at the summit.

If you're keen to learn more from Doina and other global experts such as Yoshua Bengio, Full Professor at Université de Montréal, Hugo Larochelle, Director at Google Brain Montreal and Inmar Givoni, Senior Autonomy Engineering Manager at Uber ATG, register for an Early Bird discounted pass to the summit now.

Deep Learning Summit, Montreal 2019