Concepedia

Generative Knitting Design

Generative Knitting Design is a computational design methodology within textile engineering that systematically produces knitting patterns and structures through algorithmic rule sets or data-driven models, distinguished by its capacity to autonomously generate novel, complex, and often customizable textile outputs based on parametric, stochastic, or learned design constraints.

3

Publications

284

Citations

8

Authors

4

Institutions

Publications per year

2017–2026

1

Parents

Publications

3

1–3 of 3

Authors

8

  1. MH
    Megan Hofmann

    Carnegie Mellon University, United States

    1 publications · 27 citations

    1

    h-index

  2. JE
    Jenny E. Sabin

    Cornell University, United States

    1 publications · 19 citations

    1

    h-index

  3. KH
    Kok Hoong Leong

    University of Malaya, Malaysia

    1 publications · 238 citations

    1

    h-index

  4. ZH
    Zheng‐Ming Huang

    Tongji University, China

    1 publications · 238 citations

    1

    h-index

  5. GB
    G.A. Bibo

    Queen Mary University of London, United Kingdom

    1 publications · 238 citations

    1

    h-index

1–5 of 8

Institutions

4

  1. National University of Singapore

    Singapore, Singapore

    1 h-index

    2 publications

    476 citations

  2. Carnegie Mellon University

    Pittsburgh, United States

    1 h-index

    2 publications

    54 citations

  3. University of Washington

    Seattle, United States

    1 h-index

    1 publications

    27 citations

  4. Cornell University

    Ithaca, United States

    1 h-index

    1 publications

    19 citations

1–4 of 4

Venues

  1. ACADIA quarterly

    1 publications · 19 citations

    1

    h-index

  2. 1

    h-index

1–2