Program Overview

Data Science, PhD

Degree Awarded:

Doctor of Philosophy in Data Science

Chairs:

Joseph Mitchell, Samir Das

Director:

Zhenhua Liu

Coordinator:

Christine Rota

Office:

Math Tower Rm P-138 & 1-106

Program Website:

The SBU Graduate Program in Data Science (DAS) features both MS and PhD degree programs in Data Science. It is jointly offered by the Department of Applied Mathematics and Statistics (AMS), and the Department of Computer Science (CS), both part of the College of Engineering and Applied Sciences (CEAS). Students will receive vigorous training in Data Science encompassing topics such as statistical analysis, big data analysis/management and fundamentals of computing.

Admission Requirements

Applying to the Program

We welcome students with solid foundations in data science, computer science, statistics, mathematics, or related science or engineering disciplines to apply for our program. General application information can be obtained at the Graduate School website.

Application Requirements

• A bachelor’s degree in computer science, data science, statistics, mathematics, a natural science, engineering, an applied science, or social science with a strong mathematics and Students are expected to be fluent in Calculus and at least one programming language.
• A minimum overall cumulative GPA of at least 3.0 (or equivalent), and at least a 3.0 average in all courses in pertinent or related fields. Attention will be given to courses related to data science, computer science, statistics, and mathematics.
• For Fall 2023 applications, the Graduate Record Examination (GRE) General Test is NOT required. However, you are most welcome to submit your GRE score should you have it.
• An applicant who is not a native or primary speaker of English must present a minimum score for either the TOEFL or IELTS tests as follows:
  • TOEFL iBT: Overall score of 90 for doctoral applicants and 80 for master’s applicants.
  • IELTS: Overall score of 6.5, with no subsection recommended to be below 6.
• Three letters of reference and all transcripts of undergraduate and/or graduate study completed.
• Applicants with domestic credentials must submit an official transcript from each undergraduate college or university attended, regardless of whether a degree was conferred. Applicants must also submit an official transcript from each college or university relating to graduate-level work, regardless of whether a degree was conferred.

Provisional Admission

Occasionally, students with who are less proficient in terms of credentials, but otherwise demonstrate academic potential are offered provisional admission. Their admission offer will stipulate remedial classes they must take in their first semester and earn at least a B average in order to matriculate to the regular MS or PhD student status.

Degree Requirements

The doctoral students in Data Science are required to take the same 10 core courses as in the MS program, as well. Furthermore, the doctoral students will need to take at least 2 electives (any letter-graded courses) from AMS or CS departments, plus an additional 42 credits of electives (including at least 18 thesis research credits) to satisfy the minimum 78-credit PhD program requirement.

Notes:

• The program provides a pathway for MS students to transfer to the PhD program upon completing the set of eight core courses with GPA> =3.5 and passing the doctoral qualifying exam.

Financial Support

All students admitted to the PhD program will automatically be considered for financial support and tuition waiver if the application is submitted by the due date. MS students are not typically considered for financial support or tuition waiver at the time of admission. However, in a small number of cases qualified MS students are able to receive partial support via departmental or campus opportunities.