NYU University-wide Initiative in Data Science

Everywhere around us, data are being collected at unprecedented speed and scale — from online social networks and ecommerce sites to sensors in laboratories and smart utility meters.

In order to unlock the powerful potential of this big data, the world needs researchers and professionals skilled in developing and utilizing automated methods of analyzing it. These individuals are called “data scientists,” and we are revving up efforts to meet industry’s and academia’s demand for them.

We have launched a university-wide initiative in data science in order to establish the country’s leading data science training and research facilities.

Our initiative is university-wide because data science has already started to revolutionize most areas of intellectual endeavor found at NYU and in the world. We believe this revolution is just beginning. Data science is becoming a necessary tool to answer some of the big scientific questions and technological challenges of our times: How does the brain work? How can we build intelligent machines? How do we better find cures for diseases?

Data science overlaps multiple traditional disciplines at NYU such as mathematics (pure and applied), statistics, computer science and an increasingly large number of application domains. It also stands to impact a wide range of spheres — from healthcare to business to government — in which NYU’s schools and departments are engaged.

Resources

The intellectual resources required to undertake NYU’s university-wide initiative in data science will come from researchers and professors across our 18 schools and colleges. Research centers at the forefront of their fields in technical and scientific areas as well as in the social sciences and humanities will contribute new insights and perspectives. Three important centers are leading the way:

Computing power and data storage resources are critical to the Data Science Initiative. NYU and NYU-Poly, our engineering institute, have substantial computing resources already, including supercomputing facilities, long-term data storage and high-end computing labs. NYU plans to invest further to expand these resources.

Synergies

Data science is truly interdisciplinary. While mathematics and computer science are at its core, skills and advances in other disciplines are vital to its success. Improved hardware engineering, for example, can help gather and process data more efficiently. Graphic and instructional design can make findings easier to communicate and understand.

Varied disciplines and industries also stand to benefit from the knowledge data science can illuminate. Virologists, for example, can better predict outbreaks. Managers can make business decisions informed by deeper insights from data instead of just intuition.

The nature of the research and education programs the university-wide initiative in data science will undertake will be similarly interdisciplinary. Our integrated approach means that schools, departments, and research centers from across NYU will collaborate, sharing their expertise and generating the fresh perspectives that arise when multiple disciplines work together.