MisMatch: A Sustainable Fashion Solution
Salwa Mehreen
BIO: I am an international student from Sylhet, Bangladesh, currently studying Computer Science at Whitworth University. Ever since fifth grade, I’ve been fascinated by robotics, which later grew into a love for coding and game development. That passion eventually brought me to Whitworth, where I’ve spent the last three years learning, growing, and building projects that blend creativity and technology.
MAJOR: Computer Science
Minor: Business
Outside of tech, I love drawing — even though I’m terrible at it and I’m a proud Taekwondo black belt. I miss the adrenaline of competing in national championships, but the discipline and spirit still stay with me.
My journey at Whitworth has been incredible, thanks to the constant support and encouragement from my amazing professors. Through leadership roles on campus and technical internships during the summers, I learned to navigate the professional world with confidence. I’m grateful to have received an Honors Scholarship from Whitworth and the Schweitzer Engineering Laboratories Scholarship. Whitworth also introduced me to entrepreneurship, and I was honored to represent North America as a finalist for my project in the Founders Live competition. After graduation, I plan to continue my journey as a software engineer and eventually launch a startup of my own!
Project Overview: My project, MisMatch, started from a real-life frustration — how much time and energy it takes just to pick an outfit. Research shows that people spend around 102 hours a year deciding what to wear (Marks & Spencer), and about 50% of Americans say it’s the most stressful part of getting ready for an event (Trunk Club). At the same time, the fast fashion industry produces around 92 million tons of textile waste each year (UNEP), most of which ends up in landfills. I wanted to create something that helped people in their everyday lives while also promoting more sustainable habits. MisMatch is all about making outfit decisions quicker, boosting confidence, and encouraging people to use and love the clothes they already own instead of buying more.
The app brings together several features to make this happen. All a user needs to do is enter a few details — the event or occasion they’re dressing for, personal information like skin tone and undertone, and even the current weather — and MisMatch suggests outfit combinations pulled straight from their existing digital closet. AI-driven recommendations help match colors, styles, and proportions to what suits the user best. The wardrobe is built easily using image recognition (YOLOv5), where users can just snap photos of their clothes instead of typing everything manually. There’s also a sharing and clothing exchange feature that encourages users to swap items instead of shopping for new ones. Originally, I had planned to include a virtual try-on feature powered by AR — the idea was to let users overlay outfits onto themselves through their phone’s camera, helping them “try on” different looks without physically changing over and over. I explored multiple platforms, but due to the high costs and complicated integration, that feature had to be put on hold for now. Even so, MisMatch stays focused on helping people save time, reduce stress, and make smarter, more sustainable fashion choices.