Massachusetts Institute of Technology (MIT) has unveiled a game-changing innovation in sustainable apparel: the Refashion software, launching to the public from Cambridge, MA, on October 16, 2025. Developed by researchers in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Adobe Research, this tool enables designers and novices to create modular clothing—garments meant to be repeatedly reconfigured, resized, and restyled using simple, interactive blueprints.
Tackling Fashion Waste with Modular Design
The fashion industry generates over 92 million tons of textile waste annually, fueled by discarded garments that fall out of style or no longer fit. With Refashion, MIT aims to address this crisis head-on. They wanted to create garments that consider reuse from the start. Most clothes you buy today are static, and are discarded when you no longer want them. Refashion instead makes the most of our garments by helping us design items that can be easily resized, repaired, or restyled into different outfits.
Unlike conventional apparel, Refashion designs begin as visual diagrams—users draw, combine, and customize modular shapes on a simple grid interface. These modules form building blocks for garments, such as a pair of pants convertible into a dress, or a shirt with an attachable hood for rainy days.
How It Works: The Refashion Interface
Refashion presents a straightforward Pattern Editor tool.Users connect dots on a grid to outline each garment’s component panels.Custom shapes and templates are provided for basics like T-shirts, blouses, or trousers.
Each piece is divided into numbered blocks that can be dragged onto a 2D mannequin, showing how modules combine and connect.Patterns are visualized on 3D models of diverse body types; users can also upload personalized avatars.The software generates a digital blueprint, allowing users to extend, shorten, and recombine modules, keeping clothing adaptable for multiple occasions and life stages (e.g., maternity wear, formal attire, seasonal layering).
A New Era of Accessible and Sustainable Fashion
Early user studies demonstrated Refashion’s impact:
- Both professional designers and novices created prototypes ranging from asymmetric tops to multi-functional jumpsuits—often in under 30 minutes.
- The system lowered barriers to garment prototyping, enabling accessible experimentation and rapid iteration.
- “Rebecca’s work is at an exciting intersection between computation and art, craft, and design,” says MIT EECS professor and CSAIL principal investigator Erik Demaine, who advises Lin. “I’m excited to see how Refashion can make custom fashion design accessible to the wearer, while also making clothes more reusable and sustainable.”
Refashion’s Sustainable Vision
The software’s modularity means users can design apparel with reuse in mind. Pieces can be updated as trends evolve, or personalized for changes in fit, function, or personal style. Yesterday’s scarf could be today’s hat, and today’s T-shirt could be tomorrow’s jacket. This approach marks a shift away from static garments toward reuse by design.
Expert Perspectives: The Promise and Potential
This is a great example of how computer-aided design can also be key in supporting more sustainable practices in the fashion industry. By promoting garment alteration from the ground up, the MIT team developed a novel interface and optimization algorithm that helps designers create garments with longer lifespans through reconfiguration.
Future Outlook and Applications
Rebecca Lin and the CSAIL-Adobe team are improving Refashion’s usability and planning integrations with material selection algorithms. Projects supported by MIT’s Morningside Academy for Design, an MIT MAKE Design-2-Making Mini-Grant, and the Natural Sciences and Engineering Research Council of Canada aim to optimize the system for industrial-scale sustainability.
Refashion was presented at the ACM Symposium on User Interface Software and Technology in October 2025, drawing interest from designers, sustainability advocates, and leading fashion houses interested in modular, data-driven design.
