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Call for Posters: INFORMS Conference on Quality, Statistics, and Reliability (ICQSR)

  • 1.  Call for Posters: INFORMS Conference on Quality, Statistics, and Reliability (ICQSR)

    Posted 03-06-2023 23:14
    Edited by Simon Mak 03-06-2023 23:14

    Call for Posters

    Poster Session and Best Poster Competition

    INFORMS Conference on Quality, Statistics, and Reliability (ICQSR)

     

    The 2023 INFORMS Conference on Quality, Statistics, and Reliability (ICQSR) invites poster presentations in all areas of quality, statistics, and reliability. The Best Poster Award Competition will be held at the session to recognize excellence among the high-quality posters. This award program brings prestige to the QSR Section as well as to the recipients of this honor.

    Conference dates: June 06 – 08, 2023

    Location: Raleigh, North Carolina, United States

    Conference website: https://informs-qsr.wordpress.ncsu.edu/

    The INFORMS Conference on Quality, Statistics, and Reliability (ICQSR) is the flagship conference of the Quality, Statistics, and Reliability (QSR) section of the Institute for Operations Research and the Management Sciences (INFORMS). ICQSR aims to provide an international forum for exchanging research innovations and advancements that reinforce the scientific essentials – quality improvement, statistical learning, and reliability assurance – and embrace emerging practical challenges. The theme of ICQSR 2023 is Artificial Intelligence (AI) and Analytics for Future Industry.

    On behalf of the organizing committee, we would like to invite researchers, practitioners, and students to share their projects presented as poster displays. All topics related to quality, statistics, and reliability are welcome. The poster can be about original research, new developments, novel concepts, state-of-the-art review/survey, case study, implementation, software, etc.

    Eligibility Requirements:

    • At least one of the authors must be a member of the QSR Section (Link to join QSR).
    • The primary author or one of co-authors must register for the conference and must be committed to presenting the poster during the poster session of the conference.
    • Only one poster submission will be permitted per presenting author.

    Submission Process:

    Step 1.     Abstract Submission. The following items are needed by March 31st, 2023: contact information for yourself and any co-authors, affiliation and short bio of the presenting author, title and abstract of the poster. Submit using the following link: https://urldefense.com/v3/__https:/forms.gle/VtMGvTWy2D7rE9ib8__;!!LkSTlj0I!Fm7Ys1p9VEetW-EF_lTtlqNDyvw6wOd6ZR1iiS2KBKrVVkVyuhu03u0jVBXRAhgURH4P0T_6bGL6xiAab0gaXjI$ Click to follow link." target="_blank" rel="noopener">https://forms.gle/VtMGvTWy2D7rE9ib8.

    Step 2.     Poster Review for Competition and Scheduling. Authors will be notified of acceptance by April 15th, 2023, with further instructions on poster preparation. The Organizing Committee will screen the poster submissions to assign to judges and determine the presentation time accordingly. The schedule will be announced before the conference.

    Step 3.     Poster Submission. The PDF document of the poster must be submitted by June 1st, 2023.

    Step 4.     Poster Session and Competition. Presenters will bring a hard copy of the poster to present at the ICQSR Best Poster Competition Session. All posters presented in the Poster Session will enter the Best Poster Award Competition automatically. Judging will take place live by a panel of distinguished "celebrity judges". The winners will be announced at the 2023 ICQSR Banquet. 

    The committee of the ICQSR Best Poster Competition:

    Weihong (Grace) Guo, Ph.D. (Chair)

    Associate Professor, Department of Industrial and Systems Engineering, Rutgers University-New Brunswick

    Email: wg152@soe.rutgers.edu

    Qianmei (May) Feng, Ph.D.

    Professor and Brij and Sunita Agrawal Faculty Fellow, Department of Industrial Engineering, University of Houston

    Email: qfeng@central.uh.edu

    Simon Mak, Ph.D.

    Assistant Professor, Department of Statistical Science, Duke University

    Email: sm769@duke.edu



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    Simon Mak
    Assistant Professor
    Department of Statistical Science
    Duke University
    Website: https://sites.google.com/view/simonmak/
    Office: Old Chemistry 112A

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