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  • 1.  6th Annual DoD AI/ML TEM

    Posted 08-31-2022 17:57

    (Note: The following information is credited to Dr. Kelly Neville from MITRE for sharing)

    Please find below the call for registration and presentations to the 6th Annual DoD AI/ML TEM. Participation is limited to those who work in the DoD, FFRDCs, or UARCs. It would be terrific to have representation from HFES and HART members as attendees and presenters.

    v/r,

    Kelly

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    6th Annual DoD AI/ML TEM
    18 - 19 October 2022

    (1200 - 1700 EDT daily)

    PARTICIPATION: This Technical Exchange meeting (TEM) is jointly sponsored by the OSD(R&E) C4I and Autonomy Community of Interests (CoIs). The mission of this event is to identify opportunities and facilitate discussions leading toward the development and enhancement of working-level collaborations in Artificial Intelligence (AI) and Machine Learning (ML) within and across DoD organizations, and federally funded and university-affiliated research centers.  This year we would like to highlight AI/ML research that is being done by FFRDCs, and UARCs, and we welcome participation by personnel who are interested in sharing their current research efforts in AI/ML.  We would also like to welcome back presenters and attendees from past years, and encourage you to share this invitation with other DoD/FFRDC/UARC AI/ML researchers within your organization whom you feel may have research efforts to share.

    EVENT FORMAT:  VIRTUAL. This event will be accessible via ZoomGov (IL4 DoD approved platform), with presentations organized into parallel, themed tracks. The virtual meeting links and any further instructions for TEM attendees and presenters will be distributed to registered participants prior to the event.

    CLEARANCE LEVEL/SECURITY:  This event is unclassified, but some of the tracks will have limited participation because the information is restricted by DoD guidelines of Controlled Unclassified Information (CUI)/Controlled Technical Information (CTI). As such, only personnel who are vetted as DoD military/civilian personnel or fall in the category of DoD contractors (FFRDCs or UARCs) with proof of US citizenship and employer may attend the DoD distribution-restricted sessions. Please see the registration form for more details on how to submit your US citizenship/employment verification.

    REGISTRATION:  Online registration is required before 16 Sep 2022 at:  https://app.smartsheet.com/b/form/e787a74a9e1b49dfbf7a9e2feef0a6c0

    CALL FOR PRESENTATIONS

    We are inviting researchers who are interested in presenting their research efforts at the TEM to please indicate your interest on the registration form and provide the information requested about your research project. Presentations should be technical in nature and cover current or recent AI/ML TEM efforts of interest to DoD. Specific details regarding the technical program and presentation format and length will be sent to registered presenters once they have been determined.  Before uploading your presentation, please ensure that your presentation material contains a distribution statement, even if it is approved for public release. Presentations that are not approved for public release should be marked in compliance with current guidance for marking and handling Controlled Technical Information (CTI) in accordance with Department of Defense Instruction 5200.48, "Controlled Unclassified Information (CUI)". Briefing slides will be shared with TEM participants in accordance with their DoD controlled dissemination statement.

    Your presentation should be uploaded before 23 Sep 2022 via the secure portal at:  https://app.smartsheet.com/b/form/e5e8b67a511d448e80d8c72856a0d4c1

    KEY DEADLINES:

    • 16 Sep 2022:  All registrants should submit their Registration and US Citizenship/employment verification information as soon as possible, but no later than 16 Sep.
    • 23 Sep 2022: TEM presenters should submit their Presentation materials on or before 23 Sep.

     

    AI/ML TEM on DoDTechipedia:  https://www.dodtechipedia.mil/dodwiki/x/DQCrM

    Please note that use of the AI/ML TEM wiki site is not mandatory for participation, as any necessary materials will be emailed to AI/ML TEM registrants before the event.

    • DoD employees and DoD contractors with CACs: We will be posting the TEM agenda, meeting links, and any relevant information for the AI/ML TEM on the DoDTechipedia wiki site, which is restricted to DoD employees and DoD contractors with CACs. Further restrictions may apply to DoD contractors on some pages due to CUI/CTI dissemination restrictions.
    • The DTIC site requires a CAC to log in, and there is a short registration process the first time you try to access the DoDTechipedia wiki site. If you have never used DTIC before, you will first need to register with DTIC: https://www.dtic.mil  and then go to the DoDTechipedia wiki site. It is recommended that you register for access to the site well before the event to ensure you will be able to access the agenda, program, and other materials during the TEM. Anyone experiencing access issues, please contact the
      DTIC Helpdesk:  dtic.belvoir.us.mbx.dtic-access@mail.mil  | Phone: 800-225-3842  
    • DoD employees and DoD contractors without CACs: TEM agenda, program with meeting links, and any necessary information will be distributed to all registrants via email prior to the event.

    We look forward to this year's event and to hearing about your AI/ML research efforts!  If you have questions about the event, please feel free to contact Ms. Ellen Kennedy at: ellen.kennedy.ctr@us.af.mil.

     

    MARK H. LINDERMAN, PhD, ST

    Air Force Lead for OUSD(R&E) C4I Community of Interest

    Chief Scientist, AFRL Information Directorate

     

    LEE M. SEVERSKY, PhD

    Air Force Lead for OUSD(R&E) Autonomy Community of Interest Foundational AI Working Group

    AFRL Autonomy, Command & Control Portfolio Lead

    AFRL Information Directorate



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    Lixiao Huang, PhD
    HART TG Chair
    Associate Research Scientist
    Arizona State University
    lixiao.huang@asu.edu
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