Monday, September 19, 2022

[DMANET] Deadline extended: ACM/IEEE International Workshop on Quantum Computing


Call for papers: ACM/IEEE International Workshop on Quantum Computing

The ACM/IEEE International Workshop on Quantum Computing is a forum that
brings together researchers and practitioners interested in quantum,
hybrid quantum-classical and quantum inspired computing. Sponsored by
ACM and IEEE, the workshop seeks to act as a conduit for the
presentation of recent research results in all areas of quantum
computing. Papers reporting on initial results or work in progress as
well as papers discussing mature research projects or case studies of
deployed systems are sought out. Submissions describing big ideas that
may have significant impact and could lead to interesting discussions at
the workshop are encouraged.

Topics of interest include but are not limited to: quantum algorithms,
applications of quantum computing, quantum machine learning, quantum
optimization, quantum blockchain, quantum software development,
gate-based quantum devices, quantum annealers, digital annealers,
quantum network, quantum security, quantum Internet. The keyword
"quantum" refers to pure quantum, hybrid quantum-classical and quantum
inspired approaches and technologies.

Authors should follow the IEEE guidelines when preparing their
contributions (maximum paper length: 6 pages with 10-pt font:

Workshop website:
Submission site:

At least one of the authors of each paper accepted for presentation in
Quantum 2022 must register for the workshop. All papers presented at the
workshop will be included in the IEEE Digital Library.

Important Dates
Deadline for Submission: September 23, 2022, (AOE)
Notifications of Acceptance: October 5, 2022 (AOE)
Camera-ready Paper Submission: October 14, 2022 (AOE, firm)
Workshop Date: December 5, 2022

Workshop Organizers:
Qun Li, William and Mary, USA
Xiaoyuan Liu, Fujitsu Research of America, USA
Ilya Safro, University of Delaware, USA

Technical program committee:
Yuri Alexeev, Argonne National Lab
Nai-Hui Chia, Rice University
Lukasz Cincio, Los Alamos National Laboratory
Thang N. Dinh, Virginia Commonwealth University
Yu Du, University of Colorado Denver
Alexey Galda, Menten AI
Dylan Herman, JPMorgan Chase
Rebekah Herrman, University of Tennessee Knoxville
Ang Li, Pacific Northwest National Laboratory
Qun Li, William & Mary
Xiaoyuan Liu, Fujitsu Research USA
Phillip Lotshaw, Oak Ridge National Laboratory
Danylo Lykov, University of Chicago
Catherine McGeoch, DWave
Ilya Safro, University of Delaware
Yiyu Shi, University of Notre Dame
Yuan Su, Microsoft Quantum
Tamás Terlaky, Lehigh University
Davide Venturelli, NASA
Jonathan Wurtz, QuEra Computing

Prof. Ilya Safro
Department of Computer and Information Sciences
Department of Physics and Astronomy
Data Science Institute
University of Delaware

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