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Xpress Best Paper Award

Terms and Conditions

These Xpress Best Paper Award Terms and Conditions (“Terms and Conditions”) apply to the FICO Xpress Best Paper Award described at I²DAMO contest webpage. By participating in the FICO Xpress Best Paper Award, you (“you,” “participant,” or “author”) agree to these Terms and Conditions.

Description. The Xpress Best Paper Award is an annual competition that recognizes outstanding papers in the area of operations research, mathematical optimization, and related fields, using FICO Xpress Optimization products. FICO may change or cancel the Xpress Best Paper Award at any time by providing notice at I²DAMO contest webpage.

 

Cash Prize Award. A cash prize in the total amount of $1,500 will be awarded to the author(s) of the winning paper. The cash prize is not transferrable or assignable. The winning author(s) is responsible for any potential tax implications of the cash prize.

 

Judging Criteria. The winning paper will be selected by a five member award committee as announced on I²DAMO contest webpage. The winning paper will be selected by the award committee, in its discretion, based on judging criteria that includes the significance of the contributions to research and its advancement, originality and innovation of ideas and methods, real world application, and quality and clarity of exposition. If the committee determines that no paper submitted meets these criteria, then no award will be given by the award committee. 

 

Eligibility. To be eligible, a paper must have been published in English in a peer-reviewed journal, or in a comparable, well-referred volume, between January 1, 2022 and December 31, 2023. Online first publications in named journals or volumes are eligible. The paper must be based upon usage of FICO Xpress Optimization products. Papers authored or co-authored by FICO employees or their family members, or by members of the award committee or their family members, are not eligible. An individual participant may be an author or co-author on only one paper submitted. Persons subject to sanctions restriction or located in countries subject to embargo by the governments of United States, Canada, United Kingdom, or the European Commission or its member states, are not eligible to participate. Participants must me 21 years of age or older to participate.

 

Submission Requirements. To be considered, the submission must include a copy of the paper, a citation to the publication of the paper along with the date of publication and a short statement describing the use of FICO Xpress Optimization products. Submissions must be sent to: This email address is being protected from spambots. You need JavaScript enabled to view it. (Subject: Xpress Award Application / Applicant name).

 

Submission Deadline. Submissions must be received by January 31, 2024.

 

No Purchase Required. No purchase is required to participate in the competition. Persons interested in participating who do not have access to FICO Xpress Optimization products (such as through their employer or educational or research institution) may submit a written request for product access. The request must include the person’s name; name of employer, educational institution, or professional association; and description of the proposed paper and  use of FICO Xpress Optimization product. Product access will be made available if, after evaluation by the award committee, the written request is determined to be consistent with the purposes of Xpress Best Paper Award. Such access will be provided only for the purpose of participating in the competition.  

 

Winner Blog Submission. The author(s) of the winning paper will be obliged to contribute a two-page popular scientific write-up of their research results to be published in the FICO Optimization Blog.

 

Consent to Use. By submitting the paper, the winning author grants FICO the right to use and publish the winning author’s name, publication title and bibliographic information, and a summary of the winning paper, on FICO’s website and in FICO blog posts and in other media and/or distribution formats, including for marketing, advertising, publicity, educational, sales, trade, and promotional purposes, with no right of approval and no right to compensation other than the cash prize award.

 

Data Privacy. By entering the Xpress Best Paper Award, you understand that FICO may collect certain personal information about you in connection with your participation. This personal information may include your name, contact information, and employment, educational or research institution, and other professional information. You consent to the collection, use, and disclosure of your personal information in accordance with FICO’s Privacy Policy (http://www.fico.com/en/Pages/Privacy.aspx). You agree that FICO may use your personal information in connection with, and to contact you about, the Xpress Best Paper Award.

Compliance. In connection with your participation in the Xpress Best Paper Award, You agree to comply with all applicable laws and specifically agree not to submit any material or information or otherwise engage in any conduct that is: (i) defamatory, infringing, misleading, or otherwise illegal; or (ii) protected by intellectual property, trade secret, or property or privacy rights of any other person or entity unless You own or control the rights thereto or have received all necessary permissions. You also agree to comply with, and hereby confirm that your participation in the Xpress Best Paper Award does not violate the policies of your employer or research or academic institution, including any policies relating to ethics, code of conduct, gifts, taxation, and personal income. You agree to indemnify, defend and hold harmless FICO from and against any and all third party claims, damages, liabilities, costs and expenses (including reasonable attorneys’ fees) arising from a violation of the obligations set forth in this section.

  • I²DAMO
    Intelligente Integrierte Datenanalyse und
    Mathematische Optimierung GmbH

  • Managing Directors:
    Arne Schröder 
    Ines Höschel

Project Partner of: