Call for Submissions: 
Let Us Find Our Way Home

Let us find our way home is a community weaving and machine learning project that brings together local and global communities to visualize the collective concept of home.

The public is invited to express interpretations of home as both a physical and emotional space through weavings and accompanying texts. Weavings will be pieced together as they accumulate. Machine learning — the use of algorithms to interpret and predict data — will be applied to anonymize individual responses and generate a collective manifesto on the concept of home.

By interpreting commonalities and patterns across the woven and textual submissions, the project aims to articulate how we individually connect to home in hopes that, together, we can build a space for ourselves and explore the idea of belonging.

Free tapestry weaving workshops will be hosted by Chi Nguyen during open community hours between February 23 and April 1, 2018 on:

Wednesdays, 6-8pm
Fridays, 12-3pm
Saturday, 12-5pm

Location: Bard Graduate Center Gallery
18 W 86th St, 4th Floor New York, NY 10024
Accessibility: The event will have a wheelchair accessible entrance, elevator, and wheelchair accessible restroom.

Weaving workshops are open to people with different abilities and weaving skills.

People living outside of New York City can also participate online by submitting texts through a Google form and by mailing in their 5x5” woven pieces to:

Chi Nguyen, TAC Maker Space
505 Carroll St
Brooklyn, NY 11215


Public Submissions and Work-in-Progress


Data Privacy

People within marginalized communities are often targets of cyber surveillance. Images, videos, audios, texts, and other data formats submitted through the Google form can be traced back to the original owners. 

If you are concerned about data privacy and safety, please consider attending the workshop in person and/or submitting your weaving and interpretations via mail. Your name and return address on the envelope will be shredded upon receipt unless you have indicated interest in being recognized by the project. 

Sometimes, the safest way to protect your data is to not share them at all. This project strives to make space for the missing storylines from those who do not feel safe in sharing them.