The PhD program in network science aims to enhance our understanding of networks arising from the interplay of human behavior, sociotechnical infrastructures, information diffusion, and biological agents. This is an intrinsically multidisciplinary activity, with members of the network science community representing various fields including computer science, information science, complexity, physics, sociology, communication, organizational behavior, political science, and epidemiology. This doctoral program trains students in network science across several colleges—the College of Social Sciences and Humanities, the College of Science, the Khoury College of Computer Sciences, and the Bouvé College of Health Sciences. See other collaborating colleges’ catalog sections for possible elective courses.
Coursework depends on a student’s area of research and is subject to prior approval by their faculty advisor. Required coursework includes 20 semester hours of core courses in network science, plus an additional 20 semester hours of courses relevant to the students' area of research. A minimum of 40 semester hours of coursework is required, though the graduate program committee may recommend additional coursework based on student research interests.
Annual Review
A review of satisfactory progress will be ongoing and formally evaluated at the end of the program's first and second years. Students must maintain a cumulative grade-point average of 3.000 or better in all coursework. Students are not allowed to retake courses. A student who does not maintain a 3.000 GPA, or is not making satisfactory progress on their dissertation research, may be recommended for dismissal by the graduate program committee.
Each student will have a primary dissertation advisor from the network science doctoral program faculty. The dissertation advisor should be selected by the end of the program's second year's spring semester.
The dissertation committee consists of at least four members: the dissertation advisor, one additional network science doctoral program faculty member, one member expert in the specific topic of research (can be from outside the university), and one additional tenured/tenure-track faculty member from the concentration department/conferring college. The dissertation advisor must be a full-time tenured or tenure-track member of the Northeastern University faculty.
Alternate Course Path
Students have the option to complete core coursework in their first year of study. This curriculum pathway is mandatory for students whose admitting advisor is located outside of the Boston campus and elsewhere in the Northeastern network.
Qualifying Examination
The qualification exam is an oral examination of the material covered in the core curriculum. The exam will be an hour long and consist of questions selected by network science faculty. Students will receive between 50 to 80 questions to review for one month before the exam—a subset of which will make up the exam.
All students are required to sit for the exam in the fall, typically in their third year of the PhD program. Students who fail to pass the qualifying exam on their first attempt are expected to retake it in the spring term.
Students following the alternate path may take the exam at the end of the first academic year, upon completion of the required core courses.
Students may only take the qualifying exam twice.
Dissertation Proposal
Students must submit a written dissertation proposal to the dissertation committee. The proposal should identify relevant literature, the research problem, plan, and the potential impact on the field. The proposal will be presented in an open forum before a public audience and the dissertation committee, followed by questions from noncommittee members. The written proposal must be given to committee members at least two weeks before the oral presentation. After the presentation, the student will meet with the dissertation committee to address any concerns raised in either the written proposal or the presentation. The comprehensive exam must precede the final dissertation defense by at least one year.
Students may repeat the comprehensive examination once if they are unsuccessful.
Degree Candidacy
A student is considered a PhD candidate upon completion of all required coursework with a minimum cumulative GPA of 3.000, satisfactory completion of the qualification exam, and satisfactory completion of the comprehensive exam.
Dissertation Defense
A PhD student must complete and defend a dissertation involving original network science research. The dissertation defense must adhere to the dissertation policies of the College of Social Science and Humanities.
Students who have completed required coursework with a cumulative GPA of 3.000 or better may be eligible to receive an MS in Network Science degree. In addition, students who do not qualify for the doctoral degree, but who have completed required coursework with a cumulative GPA of 3.000 or better, may be eligible to receive a terminal MS in Network Science degree. Note that no students will be admitted directly into the MS in Network Science to pursue a masterʼs degree.
- Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
- Certain options within the program may be required at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality.
Complete all courses and requirements listed below unless otherwise indicated.
Milestones
Annual review
Qualifying exam
Dissertation committee
Dissertation proposal
PhD candidacy
Dissertation defense
Core Requirements
Specializations
Complete 20 additional semester hours in one of the following specializations or another course of study with written approval from your advisor.
Computer Science Specialization
Course List | Code | Title | Hours |
| CS 5800 | Algorithms | 4 |
| CS 6140 | Machine Learning | 4 |
| or CS 6220 | Data Mining Techniques |
Epidemiology Specialization
Course List | Code | Title | Hours |
| PHTH 5202 | Introduction to Epidemiology | 3 |
| PHTH 6202 | Intermediate Epidemiology | 3 |
Math Specialization
Physics/Theory Specialization
Social Science Specialization
Course List | Code | Title | Hours |
| NETS 7350 | Bayesian and Network Statistics | 4 |
| NETS 7360 | Research Design for Social Networks | 4 |
Independent Specialization
Course List | Code | Title | Hours |
| 6–8 |
Electives List
Course List | Code | Title | Hours |
| 12–14 |
| Algorithms | |
| Natural Language Processing | |
| Machine Learning | |
| Data Mining Techniques | |
| Special Topics in Artificial Intelligence | |
| Visualization for Network Science | |
| Special Topics in Data Visualization | |
| Graph Theory | |
| Machine Learning and Statistical Learning Theory 1 | |
| Network Economics | |
| Bayesian and Network Statistics | |
| Directed Study | |
| Topics | |
| Statistical Physics | |
| Computational Physics | |
Dissertation
Course List | Code | Title | Hours |
| Research | |
| |
| Dissertation Term 1 | |
| Dissertation Term 2 | |
| |
| Dissertation Continuation | |
Program Credit/GPA Requirements
40 total semester hours required
Minimum 3.000 GPA required
