The Innovation Application Award

The Innovation Award honors groundbreaking technological, methodological, or industrial advancements that significantly advance digital twin applications and impact.

Eligibility: Individuals, teams, or organizations demonstrating transformative innovation in digital twin research or practice.

For detailed award regulations, nomination procedures, and deadlines, please refer to the DigiTwin Awards page.

DigiTwin2026

  • Jaguar Land Rover

    Global luxury automotive manufacturer. For the Digital Twin application-oriented exploration in automotive field

  • SAIC GM Wuling Automobile Co., Ltd.

    Global automotive manufacturer advancing intelligent manufacturing through digital twin technologies. For the innovative digital twin application in automotive manufacturing

DigiTwin2025

  • SIEMENS AG

    A global technology leader and pioneer in industrial automation, whose comprehensive digital twin solutions drive innovation across entire product and production lifecycles.

  • System X Institute of Research and Technology

    A French public research institute dedicated to pioneering technological innovation and foundational advancements in the field of digital engineering.

DigiTwin2024

  • SANY Heavy Industry Co.,Ltd

    A global leader in heavy equipment manufacturing, recognized as a pioneer in adopting and implementing digital twin technology across its industrial processes.

  • Xiaomi Mobile Software Co.,Ltd

    An electronics giant and smart manufacturing innovator that leverages its IoT ecosystem to develop and deploy consumer-focused digital twin applications.

DigiTwin2023

  • RIAMB Technology Development Co.,Ltd

    A leading provider of industrial automation and smart manufacturing solutions that utilizes digital twin technology to optimize and innovate complex production processes.

  • Mathworks

    The leading developer of mathematical computing software, whose flagship products, MATLAB and Simulink, provide the essential tools for creating and simulating the core models of digital twin systems.