Symbiotically Redesigning Fashion with Artificial Intelligence 
Kazuya Kawasaki, Kotaro Sano, Kye Shimizu and Yusuke Fujihira 
Algorithmic Couture aims to democratize haute couture customization culture prevalent in the 19th century by revitalizing how we fashion our own style through personalization in the digital design process. As the demand for clothing increases in relation with the growing human population, the waste created in the fashion industry continues to grow. We are drowning in what we have made. The existing linear model created on the premise of mass production and consumption desperately calls for a change. Looking to a more sustainable future, we must reconsider the holistic cycle of fashion. Digital innovations have evolved the landscape of fashion. Ads are aggregated to match our consumption and fashion trends are forecasted utilizing our data. There is a need to realign our incentives to more sustainable values, by looking at how we design in fashion. For the past 70 years, we have been accustomed to coping with the standardized system in fashion that normalizes our bodies into different categories. But by utilizing 3D scanning technology alongside CAD software, we are able to optimize garments to the unique body types of the user, independent from the prêt-à-porter system. This service utilizes machine learning algorithms to generate an optimized modular patterned garment allowing for the user to customize the form, material, and color to match their personal style. By utilizing machine learning algorithms, an optimized fashion pattern is generated from the users body size and customizable design parameters. The optimized pattern cutting techniques that are generated are comprised of rectangles and straight lines, allowing for optimization of the fabric placement through the use of genetic algorithms. Through redesigning the creative process in how we design fashion patterns, much of the fabric wasted during the process can be reduced. By reallocating the resources that would otherwise become waste, we envision a more symbiotic relationship with machine learning in the fashion design process. 
Project Lead / Fashion Designer: Kazuya Kawasaki
Design Direction: Kotaro Sano 
Technical Direction: Kye Shimizu
Machine Learning Engineering: Yusuke Fujihira (archiroid) 
Film: Tomoki Yoneyama 
Film Support: Tomoyuki Hayama 
Music: Kenta Tanaka 
Model: Tamami Ohbuchi / Miki Egashira / Shin Kayoh 
Design Support: Hanako Hirata / Yutaka Ridwan 
Adviser: Keisuke Nagami (hatra) / Dr. Daijiro Mizuno PhD (RCA)
 Special Thanks: Dr. Hiroya Tanaka PhD 
Partially supported by Center of Affection-Oriented Digital Fabrication 
(Core Institution: Keio University) for COI Program in Ministry of Education, Culture, Sports, Science and Technology in Japan.