Venice Biennale of 2008
E. Dumont & E. Desmazieres for Jakob+McFarlane
I am the founder and CEO of Shade, a semiconductor startup that commercializes a novel UV sensor that mimics the skin sensitivity. Our technology is currently being used by both top-tier academic hospitals and large publicly-traded companies. I am also a junior faculty member at the Center for Discovery and Innovation where I develop new statistical methods to analyze large datasets of outcome measures, genetic and epigenetic data.
Previously, I was a postdoctoral scientist at the Jacobs Technion-Cornell Institute in NYC, working on the early development of Shade. Before that, I got my PhD in biophysics at Columbia University working on molecular tribology. My PhD work was published in Nature Nanotechnology and I was awarded the Liu-Ping fellowship for ranking first at the department's qualifying examinations.
Finally, the picture above represents the "Conflict" sculpture which I designed for the Venice Biennale of architecture in 2008.
Starting from an idea, I raised $3.8M in funding from angel investors, early-stage venture capitalists, NIH, and NSF to hire a team of scientists and engineers. Together, we developed, validated, and commercialized a novel UV-sensing semiconductor proven to be at least 10x more accurate than competitors' sensors when measuring the UV index from a variety of different sunlight situations. Our technology is currently used by several academic hospitals across the US and Europe and global publicly-traded companies.
We also designed, sponsored, and ran a randomized clinical trial on a population at high-risk of skin cancer. A publication is in preparation.
Collectively, our sensors have measured over 3 million datapoints of personal UV exposure across thousands of people.
My research is in the physics of semiconductors, digital health, and the development of useful statistical methods to analyze large-scale datasets of complex outcome and biological data.
During my studies, I have used Bayesian statistics to cluster protein heights and neural networks to untangle signals. I am currently focusing on developing machine-learning algorithms to analyze large datasets of clinical outcomes and genetic & epigenetic datasets.
During my PhD, I discovered that in-vitro kinesin-propelled microtubules experience "molecular wear" (Nature Nanotechnology publication). I also measured the height of surface-adhered kinesin proteins as a function of their density and found that their behavior follow the "mushroom-to-brush" transition that P.G. de Gennes, Nobel Prize laureate in Physics, predicted for polymers.
UV-sensing semiconductors have been around for about 60 years but they were never designed to measure solar UV exposure with the same sensitivity as the skin's. As a result, they are very inaccurate when measuring the "UV index" from sunlight (The UV index reflects the damage on the human skin). Using machine-learning, we discovered a low-cost and accurate way of measuring the UV index, which we validated and patented. Such an accuracy usually requires using a $5,000 instrument that is at most portable.
At Shade, we have been very active in advancing the field of digital health. I have contributed to several publications in the space:
Several research groups have also used the UV sensors we commercialize to conduct their own research on patient behavior in the sun (I am not a co-author in these publications).
All my recent code is on Github.
I have given several talks and been invited as a speaker to several conferences. Below we show two of them that found they way to Youtube:
I have been several times on French cable news to speak about biotechnology and startups. Here is one video (in French)