DEBORAH ESTRIN: Health tech trained students with a deep understanding in digital technologies, in the context of this complex problem of health and health care, and in a style that is about entrepreneurship and innovation. 

TIM DELISLE: What's cool at Cornell Tech is that you take a product development lens where you explore those very deep and uncertain technologies, and you can start actually turning them from [? bleeding ?] edge to cutting edge tech. The closest thing to deep technology that we use at Datalogue is deep learning. So we implement a lot of the cutting edge algorithms that are just tracking and what's best implemented in academia, and we leverage those in commercial settings. The mission data log is to eliminate the need to prepare data and get data into the hands of the people who need it. 

SONIA SEN: I've worked almost exclusively as a software engineer, and I've felt that pain of having to deal with data science problems where you can't actually get the data to work in the way that you want it to, to answer your questions. 

DEBORAH ESTRIN: To be an effective health tech innovator, whether you're doing it in a tech company, for an insurance provider, for a hospital, for a pharma company, for a startup, you have to have that ability to understand the health context and to understand the technology deeply enough to create that next innovation. 

TIM DELISLE: We're starting to do a lot of work with big pharma, and we're helping them increase their reliance on big data sets, on new and novel data sets that they pretty much hadn't considered for developing new drugs or doing post-market surveillance of their drugs. 

JOHANAN OTTENSOOSER: To humanize that, there's 1,000 hospitals that we might need data from. And every single hospital collects data in the way that's perfect for that hospital. But when you're the drug manufacturer, and you need to do analysis of the whole ecosystem and all of the patients that are with this, you need to collect data from all of those. And we're the company that facilitates turning all of those disparate data into one that can be understood by their developer. 

SONIA SEN: Every single company wants to be data driven, and what we are evolving to and strive to be is that foundational base for every single data-driven decision that is being made. 

DEBORAH ESTRIN: What's fascinating from the guidance that you get at Cornell Tech is that the faculty might not be experts in this specific problem that you're trying to solve, but their expertise is so well ingrained in their own domain that they often ask you questions that allow you to think about different ways of solving a problem that you probably haven't thought of before. 

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