Data-driven Design Exploration

Data-Driven Design Exploration is a systematic methodology within design space exploration that leverages empirical data and analytical models to iteratively guide, inform, and refine design decisions, distinguishing itself by prioritizing data-derived insights over heuristic or simulation-based exploration.

74

Publications

3K

Citations

273

Authors

118

Institutions

Publications per year

2017–2026

58

Authors

273

  1. KL
    Kristin L. Wood

    Singapore University of Technology and Design, Singapore

    4 publications · 264 citations

    4

    h-index

  2. JL
    Jianxi Luo

    Singapore University of Technology and Design, Singapore

    4 publications · 264 citations

    4

    h-index

  3. SS
    Serhad Sarica

    Singapore University of Technology and Design, Singapore

    2 publications · 133 citations

    2

    h-index

  4. YD
    Yvonne Dittrich

    IT University of Copenhagen, Denmark

    2 publications · 33 citations

    2

    h-index

  5. CS
    Cathrine Seidelin

    IT University of Copenhagen, Denmark

    2 publications · 33 citations

    2

    h-index

1–5 of 273

Venues

  1. Journal of Mechanical Design

    8 publications · 316 citations

    8

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 48 citations

    2

    h-index

  3. Computers in Industry

    2 publications · 106 citations

    2

    h-index

  4. Journal of Computational Design and Engineering

    JCDE · 2 publications · 59 citations

    2

    h-index

  5. 1

    h-index

1–5