SBIR/STTR Research Award

SBIR Phase I:Hair Genome Project - Computational approach to classifying hair profiles and dermatological health disparities in underserved communities

Award identifier 1b61df3bcd42237643a15be3cebae1cf1f7062008125a48a731594261432393bAwarding agency National Science Foundation

Award amount

$256,000

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
TIFFANY ST BERNARD
Proposal award date
2022-03-15
Contract end date
2023-02-28
UEI
H8DXCFZ51KK2
Solicitation number
NSF 21-562
Topic code
DH

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be an inclusive platform offering individuals access to data-driven, personalized insights on hair health. Hair health plays a large factor in overall mental/physical health; however, an absence of transparent data has disproportionately disadvantaged access to quality products and care information, particularly among minority communities. This disparity has led individuals to use products and/or wear styles that adversely impact hair and scalp health. The proposed technology will bridge these gaps, providing users with hair/scalp health insights and matching them with suitable products and regimens for their hair profile and goals. At the same time, the data and user engagement with the platform can be leveraged to offer brands, healthcare providers, insurance companies, etc. with deeper insights into their customers’ hair care-related goals, pain points, and health conditions. In addition to supporting hair health, this project will mitigate the scalp and hair pathologies (e.g., alopecia, burns, breakage, contact dermatitis) stemming from ill-suited products and care practices.This Small Business Innovation Research (SBIR) Phase I project aims to develop a data-driven hair intelligence platform that uses big data to democratize hair insights for all. The technology and platform will leverage big data from peer-reviewed publications and science-backed databases as well as the users themselves, to continually refine personalized insights and understand customer needs in the context of their unique hair profile. Using proprietary algorithms, the technology will be able to seamlessly recognize and map different hair types, identify secondary unique factors (porosity, density, texture, etc.), map and analyze different ingredients in products, track and map different treatment regimens and product usage, and develop sentiment analysis, patterns, and predictions. This project will: 1) Develop training dataset and tiered algorithm for hair profile classification with high confidence; 2) Validate and refine the hair profile classification system through a comparative study with dermatology residents; and 3) Establish proof-of-concept demonstrating the connection between accurate hair profile classification and data-driven product/style recommendations to improve hair-esteem.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

3 SBIR/STTR records share this UEI (2022–2025). Reported award amounts total $1,765,613. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Science Foundation, Department of Health and Human Services

Agency intelligence

National Science Foundation

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