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    Computational Science and Engineering (CSE) is vital for scientific discovery and innovation. Emerging challenges and opportunities necessitate evolving CSE research and education to meet future demands.

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    Area of Science:

    • Computational Science and Engineering (CSE)
    • Data Science
    • Advanced Computing

    Background:

    • CSE has significantly impacted research and education over the past two decades.
    • It enables answering complex questions beyond traditional theory and experiment.
    • CSE provides cross-disciplinary algorithmic and software solutions.

    Purpose of the Study:

    • To outline challenges, opportunities, and future directions for CSE research and education.
    • To address the evolving landscape of CSE due to extreme-scale computing and data revolution.
    • To inform the expansion of CSE educational programs at all levels.

    Main Methods:

    • Analysis of current trends and disruptive developments in computing.
    • Review of the role of CSE in scientific discovery and innovation.
    • Assessment of educational needs and workforce development in CSE.

    Main Results:

    • CSE is central to modern science, engineering, and technology.
    • Extreme-scale computing and data-driven discovery are reshaping CSE.
    • There is a growing demand for CSE graduates and expanded educational programs.

    Conclusions:

    • The CSE field is transforming, requiring adaptation in research and education.
    • Educational programs must integrate computational and data science principles.
    • Addressing research challenges is crucial for effective CSE workforce development.