2021 IEEE North American School of Information Theory

About the School

The 2021 IEEE North American School of Information Theory will be held Monday, June 21 through Friday, June 25 2021.

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.

Program

The school will be a virtual event held over five days and will consists of

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

  • Students presenting their own work in poster sessions.

Lecturers

Speaker Photos 
  • Tutorial 1:
    Prof. Wei Yu, University of Toronto
    Massive Random Access and Massive MIMO

  • Tutorial 4:
    Prof. Douglas Stebila, University of Waterloo
    Post-quantum Cryptography From the Learning with Errors Problem

  • Tutorial 5:
    Prof. Lizhong Zheng, Massachusetts Institute of Technology
    Understanding Deep Learning With an Information Geometric Method

  • Tutorial 6:
    Prof. David Tse, Stanford University, Padovani Lecturer for 2020
    Operating Blockchains at Physical Limits

Program Organizers

Past Schools

Sponsors / Partners

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