Daniel Shapiro

I am CTO of Lemay.ai and running a team of AI (Artificial Intelligence), ML (Machine Learning) and deep learning researchers. We provide B2B solution architecture, commercialization, and value creation. My favorite problems are those where the solution is not obvious at the outset but very elegant in retrospect. I like to think of these types of data science problems as chess moves that are obvious when the dust settles, but a gambit at the outset. A specific example that comes to mind is applying dielectric spectroscopy to sample analysis using a convolutional deep learning model. The best project I have worked on to date is the brain stimulation medical device I designed and implemented for Nuraleve, leading a team of engineers from design to final manufacturing and approvals. It still impresses me that we got CE and Health Canada and ISO approval for a device that changes the brain. It involved years of work, and a whole lot of neural networks research. Prior to my work at Nuraleve, I was the lead developer on the assignment algorithm for zip.ca, a Canadian netflix competitor in the 2000s sending DVDs to clients via mail. I was responsible for the algorithm that decided what DVDs in the 5 distribution centers would ship to what clients. It involved a lot of retail analytics including churn and customer feedback.

I completed my undergraduate degree in computer engineering, and then a masters degree in electrical engineering, and then proceeded to complete an ML PhD in electrical and computer engineering. In parallel with my education I worked for various companies, focusing in on optimization and people management. Although I have published about 30 research articles, and was granted several patents, I'm much more interested in engineering and business than academia. Working on deep learning and optimization has been my career focus. I am a writer for Towards Data Science, and I have several patents granted in my name along with 30 peer reviewed publications.