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Award details
- Awarding agency
- National Science Foundation
- Branch
- Not reported
- Recipient company
- ILAMBDA INC
- Proposal award date
- 2023-02-15
- Contract end date
- 2023-07-31
- UEI
- N9F1HMNSKYB6
- Solicitation number
- NSF 22-551
- Topic code
- AA
Research abstract
This Small Business Innovation Research (SBIR) Phase I project will develop and leverage an innovative hybrid intelligence, i.e., a unique combination of Big Data and artificial intelligence (AI) technologies with the wisdom of crowds, to help connect and empower both independent designers and small-to-medium-sized retailers/fashion buyers (together with supply chain partners), to help bring the original, unique, trendy designs with great garment quality to fashion consumers. The project also aims to help the fashion industry to tackle some of its hardest, most critical, and most urgent challenges in overproduction and waste (resulting in environmental issues). The project will advance recommendation technology and fashion intelligence by developing novel deep learning-powered fashion recommendation models, and effectively combine and integrate human fashion experts’ input and deep learning predictions. These techniques will help match fashion retail buyers and design(er)s, with the consideration of uniqueness and exclusivity.The project will also help evaluate key aspects of the fashion designs, such as uniqueness and trendiness, and provide more accurate predictions on fashion demands and sales. _x000D_
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The key technology innovations are two-fold. First, a novel self-supervised and deep learning-powered fashion recommendation engine will effectively utilize the heterogeneous fashion data (images, text, behaviors, and sales) to help accurately match fashion buyers and manufacturers with the (new) design(er)s under style compatibility and other requirements. Second, a hybrid intelligence engine will effectively combine and integrate fashion buyers' input (votes and orders) with deep learning models to help measure fashion uniqueness, trendiness, and sales forecasts, etc., of the new designs. The project can help both designers and retailers track the trends and the demands and stay ahead of the fashion curve._x000D_
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This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
Research funding history
2 SBIR/STTR records share this UEI (2023–2026). Reported award amounts total $1,524,601. Reported amounts are not federal obligations.
Phases: Phase II, Phase I
Agencies: National Science Foundation
Agency intelligence
National Science Foundation
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