Highlights

Video Highlights

See for yourself why so many alumni of the DLRL Summer School say this experience changed the course of their careers, at a pivotal time in their professional lives.

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2023 Speakers

Yoshua Bengio Machine Learning for Scientific Discovery
Glen Berseth Robot Learning (embodied AI)
Sarath Chandar Introduction to Neural Networks
Wenhu Chen Deep learning for NLP
Stefanie Czischek AI in quantum physics
Audrey Durand Exploration-Exploitation/Bandits
Golnoosh Farnadi Intro to Ethics | Responsible AI
Marzyeh Ghassemi AI for Health
Gauthier Gidel Introduction to Optimization
Marc Lanctôt Multi-agent and Social RL
Nicolas Le Roux Policy Search
Paul Liang Multimodal AI
Dave Meger Deep RL
Margaret Mitchell Responsible AI
Marlos Machado Better experiments/methods in RL (Empirical aspects of RL)
Chris Pal Deep learning for Visual Perception
Marek Petrik Robustness & safety in RL
Doina Precup Intro to RL: Markov Decision Process and Planning
Doina Precup Intro to RL: From Planning to Learning
Dhanya Sridhar Causality
Erin Talvitie Model-based RL
Petar Veličković Intro to GNNs
Su Wang Recent advances in Generative Models and vision

Sponsor the DLRL Summer School

The DLRL Summer School is a premier opportunity for institutions, companies and organizations to play a significant role in supporting the next generation of AI talent and building a diverse and prosperous future in AI for Canada.

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“The #DLRL Summer School is a place of learning at the highest scientific level in world-changing research areas but also an opportunity for networking, creating connections which can stay for life and fuel future collaborations.”

Yoshua Bengio

Canada CIFAR AI Chair, Mila | Co-Director, CIFAR Learning in Machines & Brains Program |
Scientific Director, IVADO | Scientific Director, Mila | Professor, Université de Montréal
Kimberly Nestor

“Attending DLRL 2023 was such an enriching summer school experience! I had a great time academically and it allowed me to expand my knowledge about the field. I made lifelong friends and connections, while learning about potential internships and postdoctoral opportunities.”

Kimberly Nestor

Kyunghyun Cho

“I attended DLRL early in my career. The lectures were amazing and provided an opportunity to have close interaction among the participants, and it was at that point that I decided I wanted to continue to do research full time in the area of deep learning.”

Kyunghyun Cho

Associate Professor, New York University; Fellow in the CIFAR
Learning in Machines & Brains program, CIFAR Azrieli Global Scholar 2017-2019
D'jeff Kanda Nkashama

“What struck me the most was the commitment of the DLRL summer school organizers to foster inclusive AI. As a member of a minority visible group, I was fortunate to receive the CIFAR Inclusive AI scholarship that enabled me to participate fully in this enriching program. Throughout the summer school, I delved into various aspects of machine learning, spanning optimization, computer vision, natural language processing, as well as ethical AI and AI safety. The breadth and depth of knowledge covered were truly impressive.”

D'jeff Kanda Nkashama

Alona Fyshe

“[The #DLRL] is a wonderful opportunity to bring the AI leaders of tomorrow together for a fun and immersive learning experience. It’s also a great way to showcase the depth of AI knowledge and expertise that exists in Canada.”

Alona Fyshe

CIFAR Learning in Machines & Brains;
Canada CIFAR AI Chair, Amii, University of Alberta
CIFAR Azrieli Global Scholar 2016-2018
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