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June 4, 20260 citationsOpen Access

Iterative Co-Design, Co-Development and Co-Delivery: Accelerating S&T Productivity

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MLMary Ann LeungMHMichael HerouxRVRichard Vuduc

Key Points

  • The aim is to explore how AI impacts scientific and engineering discovery and the need for integrated strategies.
  • Presenting work from a coalition of universities, industry, and workforce leaders.
  • Proposing funded co-design projects across multiple institutions for workforce development.
  • Suggesting an ecosystem approach integrating research, education, and community building.
  • AI creates both challenges and opportunities for the workforce.
  • Integrated strategies can enhance training and education across sectors.
  • A coordinated ecosystem fosters real-time evolution of research and technologies.

Abstract

Computing has been central to scientific and engineering discovery for several decades. AI has further advanced our computing capabilities, while also creating technical and workforce challenges and opportunities. This lightning talk presents work from a cross-sector coalition spanning universities, industry, DOE laboratories, and workforce leaders. AI is transforming and disrupting, creating an inflection point that requires more than scaling existing programs; it demands integrated strategies that align research, infrastructure, data, and workforce training across sectors and geographic regions. Learners must be prepared not only to use existing tools, but also to co-develop, evaluate, deploy, and adapt emerging technologies. We suggest integrating educators and learners into a coordinated ecosystem of research, development, education, training, and community building through funded multi-institutional co-design projects that evolve in real time. Reference: https://doi.org/10.6084/m9.figshare.31564060

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Cite This Study

Leung et al. (2026) studied this question.

synapsesocial.com/papers/6a2116fad499ed480b16fe32https://doi.org/10.5281/zenodo.20452177
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