Marryam Chaudhry
About
Marryam Chaudhry is from Washington, District of Columbia, United States. Marryam is currently Chief Executive Officer at XR2LEAD, located in Washington, District of Columbia, United States. In Marryam's previous role as a CEO & Founder at Ceesquare Pvt Ltd, Marryam worked in until Mar 2012.
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Marryam Chaudhry's current jobs
◊ An EDWOSB company focused on national security, flight simulation, military, and defense innovations. ◊ Member of the Fall 2020 cohort for Defense Innovation Accelerator (DIA) by NSIN-National Security Innovation Network and Fedtech. ◊ Working with VSGI- The Virginia Serious Gaming Institute at GMU on a tactical training simulation program. ◊ Member IWRP: Information Warfare Research Project ◊ Member of NXTSL - National Security Technology Accelerator. ◊ JCP Certified by DLA (Defense Logistics Agency) ◊ Member on DIBBS (The Defense Logistics Agency (DLA) Internet Bid. Board System (DIBBS) ◊ Subcommittee Member for I/ITSEC 2021 (The World's Largest Modeling, Simulation & Training Event) ◊ A founding member of the DIN: Defense Innovation Network Mastermind Group. ◊ Committee Member of XR for Defense at VRARA. ◊ Member of DEF-Defense Entrepreneurs Forum and their project X-Works. ◊ Deputy Chair for the XR for Enterprise Group at AIXR (Academy of Extended Reality). ◊ Judge for the 4TH International VR Awards 2020 ◊ Certified as a Local Disadvantaged Business Enterprise (LDBE) by the Metropolitan Washington Airports Authority (MWAA). ◊ Authored a white paper on XR for the Water Utility Industry and was scheduled to speak at MODSIM 2020. ◊ Spoke on XR at the SPIE 2020 Conference, as part of a panel. (SPIE: international society for optics and photonics) ◊ Small, Women-owned, and Minority-owned Business (SWaM) ◊ Certified Change Management Practitioner by PROSCI ◊ Panel webinars for promoting XR technologies (AR, VR, AI, Machine Learning) via AIXR ◊ Created a proprietary instructional design model for designing AI enhanced AR/VR Learning Content. The CAP Model: Content - Assessment - Practice. It is a complete end to end learning model. The AI is embedded in CAP and it will offer a personalized learning path for each individual learner. The quicker they learn, the quicker they will progress. These branching scenarios will keep the learner engaged, as they progress.