NYU Shanghai Establishes New Data Science PhD

data science phd
Sep 20 2019

NYU Shanghai is partnering with the NYU Graduate School of Arts and Science (GSAS) and the NYU Center for Data Science (CDS) to launch a new PhD program in Data Science in the fall of 2020. The five-year program is NYU Shanghai’s eighth PhD offering, and will combine coursework with research in New York City and Shanghai. 

“Data science will become increasingly important in the years to come,” says Assistant Professor Faculty Fellow of Data Science Ling Shuyang, who will serve as a supervising faculty member in the program. “Students will have access to the rich resources at the Center for Data Science in New York and conduct research in Shanghai, a global hub in data science, IT, finance, and manufacturing.”


Shuyang Ling

Ling Shuyang, the Assistant Professor Faculty Fellow of Data Science

NYU Shanghai’s Data Science PhD students will build a solid mathematical foundation in data science, apply algorithms to solve practical problems, and most importantly, be equipped to conduct independent research, says Ling.

Like many of NYU Shanghai’s Master’s and PhD offerings, the program takes advantage of the academic resources and research communities within NYU’s global network. During their first two years in the program, PhD candidates will spend fall and spring semesters in New York, joining their peers at NYU GSAS and studying at the NYU Center for Data Science. In the summer, students will be based in Shanghai, conducting research under the supervision of NYU Shanghai faculty such as Ling. After their first two years, students will pursue the remainder of their program full-time in Shanghai. Upon graduation, students will receive their doctorate from NYU.

PhD candidates will remain a vital part of the NYU academic community throughout their five years in the program, with opportunities to attend seminars, meet established academics in the field, and network with students and faculty from other universities. They will also engage with faculty, researchers, and PhD students at NYU Shanghai’s Institute for Data Science and Artificial Intelligence, as well as graduate students enrolled in NYU Shanghai’s Master of Science degree in Data Analytics and Business Computing.

Dean of Engineering and Computer Science Keith Ross says that interdisciplinarity is a hallmark of the program. “NYU Shanghai has great faculty and students in mathematics, computer science, and artificial intelligence,” says Ross. “Because data science is at the nexus of these three fields, and because data science and its applications to finance, science, social science, and artificial intelligence are the focus of many of our faculty, NYU Shanghai is a great place to pursue data science.” 

Based in New York, the NYU CDS PhD program in Data Science is among the top-ranking doctoral programs in the field and has been recognized by the National Science Foundation. 

The program boasts a world-renowned faculty team, including leaders in the field of data science. The team consists of 16 joint faculty, 11 associated faculty, and over 50 affiliated faculty who possess strong interdisciplinary academic backgrounds, and engage in research spanning a broad spectrum of subjects such as computer science, mathematics, neuroscience, linguistics, politics, physics, biology, engineering, and business. 

Applicants accepted into the program will be fully-funded under the NYU Shanghai Doctoral Fellowship, which covers all tuition and fees, international health insurance, travel funds, and an annual stipend for PhD students at NYU Shanghai. The deadline for applications for the school year beginning fall 2020 is December 12, 2019. 

For more information about the PhD in Data Science program, visit the PhD Program in Data Science webpage and the NYU Center for Data Science PhD webpage. Read the NYU GSAS PhD in Data Science requirements to find out if you qualify, and submit your application through the NYU GSAS Application portal. For further questions and inquiries, please email shanghai.phd@nyu.edu.