Acknowledgments

🙏 Credits and Recognition

Primary Contributors

Megan Hofmann - Lead Developer and Maintainer

Primary architect and developer of the knitout-interpreter library. Responsible for design, implementation, and ongoing maintenance.

Research Institutions

Northeastern University ACT Lab

The Augmented Creativity and Textiles (ACT) Lab at Northeastern University provides the primary research context and support for this work.

  • Laboratory website: ACT Lab

  • Focus areas: Human-computer interaction, computational textiles, digital fabrication

Carnegie Mellon University Textiles Lab

The original creators of the knitout specification that this library implements.

  • Jim McCann and collaborators for establishing the knitout standard

  • Their foundational work enabled machine-readable knitting instructions

  • Papers and tools that defined the field of computational knitting

Funding Support

This work has been supported by the National Science Foundation through the following grants:

NSF Grant 2341880

Title: “HCC:SMALL:Tools for Programming and Designing Interactive Machine-Knitted Smart Textiles”

  • Program: Human-Centered Computing (HCC)

  • Award Type: Small Grant

  • Focus: Development of programming tools for smart textile creation

  • Impact: Enables the creation of interactive and responsive knitted materials

NSF Grant 2327137

Title: “Collaborative Research: HCC: Small: End-User Guided Search and Optimization for Accessible Product Customization and Design”

  • Program: Human-Centered Computing (HCC)

  • Award Type: Small Collaborative Grant

  • Focus: Making design tools accessible to end users

  • Impact: Democratizes access to computational design capabilities

Academic Foundations

Foundational Publications

The work builds upon several key academic contributions:

  • “A Compiler for 3D Machine Knitting” - McCann et al. Established the theoretical foundation for automatic knitting compilation

  • “Automatic Machine Knitting of 3D Meshes” - Narayanan et al. Demonstrated the feasibility of complex 3D knitting through computation

  • “Visual Knitting Machine Programming” - McCann et al. Introduced visual programming concepts for knitting machines

Research Community

The broader computational textiles and digital fabrication research community has provided inspiration, feedback, and collaboration opportunities that have shaped this work.

Technical Dependencies

Open Source Libraries

This project builds upon excellent open source software:

  • parglare - Parser generator library by Igor Dejanović

  • Python - The Python Software Foundation and core developers

  • Sphinx - Documentation generation framework

  • Git and GitHub - Version control and collaboration platform

Related Projects

  • knit-graphs - Fabric data structure library

  • virtual-knitting-machine - Machine simulation engine

  • koda-knitout - Optimization framework

Community Support

Beta Testers and Early Users

The library has benefited from feedback and testing by:

  • Researchers in computational textiles

  • Students in digital fabrication courses

  • Industry practitioners in automated knitting

  • Open source contributors and reviewers

Code Contributors

While currently maintained primarily by Megan Hofmann, the project welcomes and acknowledges contributions from the broader community.

Industry Connections

Machine Manufacturers

The development has been informed by collaboration and consultation with:

  • Knitting machine manufacturers

  • Industrial knitting practitioners

  • Textile industry professionals

Standards Organizations

The project aligns with and contributes to standards development in:

  • Digital textile manufacturing

  • Machine programming interfaces

  • Computational fabrication workflows

Future Acknowledgments

Ongoing Collaboration

The project continues to benefit from:

  • Active research collaboration with academic institutions

  • Industry partnerships and consultation

  • Community feedback and contributions

  • Integration with related open source projects

Call for Contributions

We welcome and will acknowledge:

  • Code contributions and improvements

  • Documentation enhancements

  • Bug reports and feature requests

  • Academic citations and research applications

  • Educational use and course integration

Contact and Attribution

How to Cite

If you use this software in academic work, please cite:

Hofmann, M. (2024). knitout-interpreter: A Python library for interpreting
and executing knitout files. Version 0.0.18.
https://github.com/mhofmann-Khoury/knitout_interpreter

Contact Information

Acknowledgment in Publications

This work should be acknowledged in publications as:

“This work used the knitout-interpreter library developed by Megan Hofmann at Northeastern University’s ACT Lab, supported by NSF grants 2341880 and 2327137.”

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Thank you to everyone who has contributed to making computational knitting more accessible and powerful through open source software and collaborative research.