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Creators/Authors contains: "Amspoker, Emily"

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  1. ; ; ; ; ; (, ACM)
    Free, publicly-accessible full text available February 12, 2026
  2. ; ; ; (, ACM)
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  4. ; ; ; ; ; (, Proceedings of the 8th ACM Symposium on Computational Fabrication)
    We show that a linear model is sufficient to accurately estimate the quantity of yarn that goes into a knitted item produced on an automated knitting machine. Knitted fabrics are complex structures, yet their diverse properties arise from the arrangement of a small number of discrete, additive operations. One can estimate the masses of each of these basic yarn additions using linear regression and, in turn, use these masses to estimate the overall quantity (and local distribution) of yarn within any knitted fabric. Our proposed linear model achieves low error on a range of fabrics and generalizes to different yarns and stitch sizes. This paves the way for applications where having a known yarn distribution is important for accuracy (e.g., simulation) or cost estimation (e.g., design). 
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  5. ; ; ; ; ; ; ; (, CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems)
    Open-source software projects have become an integral part of our daily life, supporting virtually every software we use today. Since open-source software forms the digital infrastructure, maintaining them is of utmost importance. We present Climate Coach, a dashboard that helps open-source project maintainers monitor the health of their community in terms of team climate and inclusion. Through a literature review and an exploratory survey (N=18), we identified important signals that can reflect a project’s health, and display them on a dashboard. We evaluated and refined our dashboard through two rounds of think-aloud studies (N=19). We then conducted a two-week longitudinal diary study (N=10) to test the usefulness of our dashboard. We found that displaying signals that are related to a project’s inclusion help improve maintainers’ management strategies. 
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