NYU Data Science newsletter – September 10, 2015

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“The bigger the data, the more profitable and productive predictive analytics can be.” The key word here being predictive. But what if your business is more intent on inventing the future rather than predicting it?

In this article, Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, writes that, “Innovators should look hard at how cutting-edge scientists now computationally massage their big data. ‘AI’ — artificial intelligence — is giving way to ‘AH’ — automated hypothesis. AH, not AI, will increasingly inspire tomorrow’s breakthrough innovation.”

Three major academic medical centers are combining their big data analytics forces to tackle Amyotrophic Lateral Sclerosis (ALS), a common yet poorly understood degenerative neuromuscular condition.

Johns Hopkins University’s Robert Packard Center for ALS Research, Cedars-Sinai Medical Center’s Regenerative Medicine Institute and the Massachusetts General Hospital Neurological Clinical Research Institute will coordinate research efforts to uncover the root causes of ALS, utilizing advances in genomics, precision medicine, machine learning, and pharmaceutical developments to work towards a cure for the fatal disease.

Welcome to QBioS. The Interdisciplinary Graduate Program in Quantitative Biosciences (QBioS) at Georgia Tech was established in 2015 by over 40 participating program faculty representing 7 participating Schools within the College of Sciences. We welcome applications from students interested in innovative research on living systems building upon a foundation of rigorous and flexible training. The QBioS program will prepare a new generation of researchers for quantitative challenges, new discoveries, and fulfilling careers at the interface of the physical, mathematical, computational and biological sciences. Apply by December 15, 2015 to join the inaugural class of students entering the QBioS PhD program in August 2016.

When I was at SoundCloud, I was responsible for the migration from a monolithic Ruby on Rails application to a constellation of microservices. I’ve told the technical side of this story multiple times, both in presentations, and as a multi-part series for SoundCloud’s engineering blog. These engineering bits are what people are most interested in hearing about, but recently I realised I never explained to a wider audience how we ended up using microservices to begin with.

I am sorry to disappoint my fellow techies, but the reason we migrated to microservices had to do much more with productivity than pure technical matters. I’ll explain.

… Taps and toilets alone are not enough to secure water for all.

Thankfully, this is rectified in Sustainable Development Goal #6 — Ensure availability and sustainable management of water and sanitation for all — with targets that cover water access, sanitation, hygiene, and also integrated water-resources management, ecosystems and trans-boundary cooperation. Now, with this goal, we have the chance to tackle water in a comprehensive manner. We have the potential to do it right.

We will soon have the “what” in place — it’s now time to focus on the “how.” Part of the challenge is the data. The lack of data on fresh-water ecosystems leads to uninformed decisions. Even in places where information does exist, it varies widely in quality, is difficult to locate, often expensive to access, and nearly impossible to communicate.

The University of Michigan plans to invest $100 million over the next five years in a new Data Science Initiative that will enhance opportunities for student and faculty researchers across the university to tap into the enormous potential of big data.

The opportunity to engage in cutting-edge collaborative research, the lure of being in one of the nation’s fastest growing tech hubs, the chance to work with world-class colleagues . . . there’s a long list of reasons our new faculty members are excited to be joining us. We’re every bit as excited to have them here. Read more about our latest group of talented professors below.