Hi, we’re Meghan Maupin and Sid Salvi, 2 researchers from MIT who are applying machine learning to measure skin health. Ask us anything!
Meghan and Sid, along with dermatologist Dr. Ranella Hirsch, are applying the scientific method to skin. We developed a proprietary system, Atolla, that uses machine learning to pinpoint the cause of a skin issue, and identify the right personalized solution. Skin is a complicated organ that cannot be described by just one variable. We look at people’s skin from the inside-out: how environment, lifestyle, health, other products used, and preferences all impact your skin health.
Our machine-learning algorithms recognize patterns in what’s causing your skin to react positively or negatively, and uses this information to provide you the best solution, no matter the situation. We are building a unique longitudinal dataset that is comprehensive and broad in 1) its coverage of demographics, geographies, skin concerns, lifestyles, products used, and 2) tracking of skin measurement, visual and sentiment changes. Our vision is to make a predictive model for skin, where we can predict your skin’s outcome to using a new product, or a change in environment.
After working on the technology at MIT this past year, we’ve developed an easy, at-home skin test. If you want to learn more about the Atolla Skincare System, we’re looking for early testers and feedback. Learn more here: https://kck.st/2GlmNEK.
We believe the future of skin health is data-driven. Ask us anything about MIT, machine learning, or skin health! We’d love to share what we’ve learned.
UPDATE: Thank you so much for this incredible AMA! This was a great experience and we would love to do it again. We will still monitor the thread for questions and try to respond when we can, but we're officially signing off for today.
If you're going to be at CES this January, come see Meg talk on design+tech with Core77.
More information about Atolla here: https://kck.st/2GlmNEK
Best, Meg and Sid