Computer Science

General Requirements

• Course Credit Distribution: At least 18 credits should be in CSCI-prefixed courses, with 15 or more in courses numbered 5000 and higher. Up to 12 can be in courses in other BC academic departments, and up to 15 from outside BC, including courses taken before entering the CS Ph.D. program. Credit transfer of non-BC courses is subject to approval by the Graduate Program Director or authorized representative.
• Computer Science Background Requirement: All students must have completed the equivalent of CSCI3383 Algorithms with a grade of B or higher before the end of their first year. This requirement may be satisfied by prior coursework, subject to approval by the Graduate Program Director or authorized representative.
• Computer Science Breadth Requirement: Ph.D. students must complete 3 or more credits from each of Theory, AI, and Systems, including credits at the 5000 level or above in at least two of these areas. Up to 9 credits can be waived based on the student's background, at the discretion of the Graduate Program Director or representative.
• Ethics and Society Requirement: Ph.D. students must complete a course in the broader societal and ethical dimensions of computing, such as AI, Ethics, and Society.

Research Requirements and Milestones

• Graduate research seminar: Ph.D. students are required to complete the 1-credit graduate research seminar in the Fall of their first year. The seminar includes talks by faculty and more advanced graduate students on a range of research topics and problems. 
• Research Advising: Ph.D. students should identify a research area of interest by the end of their second year and obtain the consent of a faculty expert in that area to serve as their dissertation advisor and as a member of their dissertation committee. The student and advisor should find two additional faculty who agree to serve on this committee; one of these can be a non-tenure-track faculty member, a visitor, or a member of a department other than Computer Science, possibly outside BC. 
• Research Qualifying Examination: Students must pass a qualifying examination that assesses their research readiness in their specialty area, normally by the fall of their third year. The committee will prepare two or three research questions on central and current issues in the student's area. The student will work autonomously on these questions over a roughly two-month examination period scheduled by the student and committee, and submit to the committee a written document describing their results, followed by an open oral presentation approximately one week later. The committee will assign a grade following a private oral examination of the student immediately after the presentation. 
• Ph.D. Candidacy: A student who successfully passes the research qualifying exam and completes the non-dissertation course requirements becomes a Ph.D. candidate. Ph.D. candidates must complete 6 credits of dissertation research under their advisor's supervision per semester, and meet with their full dissertation committee yearly to prepare the student for the dissertation proposal, and to assess their research progress thereafter. 
• Dissertation Proposal: Ph.D. students must obtain approval of a Ph.D. dissertation proposal before starting their fourth year, including submission of a written document and an open oral presentation about one week later. The proposed research should contribute significantly to the field and consider the work's broader impact. The dissertation committee will meet to evaluate the proposal in this light. If the required standard is not met, the student will be allowed to prepare a revised proposal. 
• Dissertation Defense: Upon completing the dissertation research, a Ph.D. candidate will schedule with their dissertation committee a date for the dissertation defense. The defense will consist of two parts: First, a one-hour public lecture by the candidate on their dissertation topic; second, a private examination of the candidate by the committee, usually no longer than one hour, to assess the substantive intellectual merit of the dissertation research at a level appropriate to the Ph.D. If the merit requirement is met, the committee members will certify their approval of the dissertation by signing the title page.

Teaching Requirements

• Graduate teaching seminar: Ph.D. students must complete the 1-credit teaching seminar in the Fall semester of their first year. This seminar helps students become more confident, effective and reflective in their teaching of computer science, prepares them for the responsibilities and challenges of serving as teaching assistants, and informs them about best practices in teaching and learning. 
• Teaching assistantship: Ph.D. students must serve as teaching assistants (TA) for two semesters. Faculty supporting several students via TA and RA positions will rotate them through the two. 
• Expository research presentation: Each CS Ph.D. student must deliver a presentation in the Graduate Research Seminar for a first-year CS graduate student audience about their ongoing dissertation research, and must serve as a teaching assistant (TA) for at least two semesters.

Financial Aid and Admissions

Financial Aid

We aim to secure support for each full-time CS Ph.D. student for five nine-month academic years, assuming satisfactory progress toward completion of the program requirements. Financial support may take different forms over time, including teaching or research assistantships. Limited summer support may be available through research or teaching positions. Students may also seek on-campus or off-campus employment during the summer.

Admissions

Applications for the Ph.D. program in CS are submitted through the Graduate School of Arts and Sciences and evaluated by the Computer Science Department's Graduate Program Committee, working with other CS faculty. Students will be admitted to the Ph.D. program, not to an individual research group. 

Illustrative Courses

Core Ph.D. Courses (typically offered yearly) 

• Foundations of Statistical Learning
• Graduate Machine Learning
• Equity and Access in Algorithms, Mechanisms, and Optimization
• Graduate Algorithms
• Graduate Theory of Computation
• Foundations of Modern Computing Systems
• Advanced Independent Study
   

Additional Graduate Courses (rotating offerings, sample) 

• Research Topics in Data Visualization
• Advanced Topics in Computer Vision
• Kernel Methods in Machine Learning
• Deep Learning for Natural Language Processing
• Advanced Topics in the Theory of Computation

For More Information About the CS Department and Ph.D. Program

Please visit the Computer Science Department Ph.D. Program page.