Optional ZOOM LINK
Meeting ID: 994 1635 8860
Passcode: 162637

To maintain data integrity in the face of network unreliability, systems rely on error-correcting codes. System standardization, such as has been occurring for 5G, is predicated on co-designing these error-correcting codes and, most importantly, their generally complex decoders, into efficient, dedicated and customized chips.

In this talk, we show that this assumption is not necessary and has been leading to significant performance loss. We describe "Guessing Random Additive Noise Decoding," or GRAND, by Duffy, Médard and their research groups, which renders universal, optimal, code-agnostic decoding possible for low to moderate redundancy settings. GRAND enables a new exploration of codes, in and of themselves, independently of tailored decoders, over a rich family of code designs, including random ones.

Hosted by Professor Peter Chin.

About the Speaker(s)

Muriel Médard
NEC Professor of Software Science & Engineering, MIT

Muriel Médard is the NEC Professor of Software Science and Engineering in the Electrical Engineering and Computer Science Department at MIT. She leads the Network Coding and Reliable Communications Group in the Research Laboratory for Electronics at MIT, and is chief scientist and co-founder of Steinwurf, and co-founder of CodeOn. She obtained three bachelors degrees and her MS and ScD from MIT. Muriel is a member of the US National Academy of Engineering and the German National Academy of Sciences Leopoldina, and a fellow of the US National Academy of Inventors, the American Academy of Arts and Sciences, and the Institute of Electrical and Electronics Engineers. Muriel is editor-in-chief of IEEE Transactions on Information Theory, and founded the Women in the Information Theory Society (WithITS) and the Information Theory Society Mentoring Program, for which she received the Aaron Wyner Distinguished Service Award. She serves on the Nokia Bell Labs Technical Advisory Board, and holds over sixty US and international patents.

Contact

For more information, contact Amos Johnson at amos.l.johnson@dartmouth.edu.