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The 2020 IEEE North American School of Information Theory will be held Wednesday, July 8 through Friday, July 10, 2020 at the University of British Columbia, Vancouver in Canada. This will be the 13th Annual North American School of Information Theory and follows a series of events designed to provide graduate students with opportunities to:

Learn from senior lecturers in the field who will present long-format tutorials;

Participate in a stimulating and inviting forum of scientists;

Present their own work for feedback and potential collaboration;

Deepen their connections with the community.

The school will be held over three days and will consists of

Senior lecturers presenting long-format (2 1/2 hour) tutorials;

Students presenting their own work in poster sessions.


Prof. Michelle Effros, California Institute of Technology
Network Information Theory

Prof. Negar Kiyavash, Georgia Institute of Technology
Causal Inference

Prof. David Tse, Stanford University
Operating Blockchains at Physical Limits

Prof. Wei Yu, University of Toronto
Massive Random Access and Massive MIMO

Prof. Lizhong Zheng, Massachusetts Institute of Technology
Understanding Deep Learning With an Information Geometric Method