To receive a PhD in Computer Science at the NYU Tandon School of Engineering, a student must:
- satisfy a breadth course requirement, intended to ensure broad knowledge of computer science,
- satisfy a depth requirement, consisting of an oral qualifying exam presentation with a written report, to ensure the student’s ability to do research,
- submit a written thesis proposal and make an oral presentation about the proposal,
- write a PhD thesis that must be approved by a dissertation guidance committee and present an oral thesis defense, and
- satisfy all requirements for the PhD degree, as described in the NYU Tandon School of Engineering bulletin, including graduate study duration, credit points, GPA, and time-to-degree requirements.
Upon entering the program, each student will be assigned an advisor who will guide them in formulating an individual study plan directing their course choice for the first two years. The department will hold an annual PhD Student Assessment Meeting, in which all PhD students will be formally reviewed.
1. Credits Requirements and Transfer Credits
In order to obtain a PhD degree, a student must complete a minimum of 75 credits of graduate work beyond the BS degree, including at least 21 credits of dissertation. A Master of Science in Computer Science may be transferred as 30 credits without taking individual courses into consideration. Other graduate coursework in Computer Science may be transferred on a course-by-course basis. Graduate coursework in areas other than Computer Science can be transferred on a course-by-course basis with approval of the PhD Committee (PHDC). The NYU Tandon School of Engineering places some limits on the number and types of transfer credits that are available. Applications for transfer credits must be submitted for consideration before the end of the first semester of matriculation. Further details can be found in the NYU Tandon School of Engineering bulletin.
2. Individual Study Plan
Each incoming PhD student will be assigned to a research advisor, or to an interim advisor, who will provide academic advising until the student has a research advisor. The advisor will meet with the student when the student enters the program to guide the student in formulating an Individual Study Plan. The purpose of the plan is to guide the student’s course choice for the first two years in the program and to ensure that the student meets the breadth requirements. The plan may also specify additional courses to be taken by the student in order to acquire necessary background and expertise. Subsequent changes to the plan must be approved by the advisor.
3. Breadth Requirement
Each PhD student must complete a breadth requirement consisting of 6 courses. To remain in good academic standing, students must fulfill the breadth requirement within 24 months of entering the PhD program.
Students who do not fulfill the breadth requirement within 24 months will be dismissed from the program, unless an exception is granted by the PHDC. The PHDC will consult with the student’s research advisor to decide whether an exception is granted and to determine the conditions the student needs to meet.
Details of Breadth Requirement
The courses used to fulfill the breadth requirement must satisfy the following:
(a) Approved list courses: At least 4 of the courses must be taken from the approved list of courses given in the appendix. The 4 courses must satisfy the following two requirements:
i) Theory requirement: At least one of the 4 courses must be taken in the Theory area.
ii) Systems & Applications Requirement: At least two of the 4 courses must be taken in Systems & Applications.
Exemptions from approved list courses: Students who have previously received a grade of A or A- in a graduate course similar to one on the approved list, while enrolled in a graduate program at a university with standards comparable to those at NYU, can use that course in lieu of taking the course on the approved list. The determination of whether a previously taken course can be used in this way will be made by the PHDC. However, any student who uses courses taken in another university to fulfill one or both of the Systems & Applications course requirements must work on a medium-size or larger software project at NYU. This project can be part of coursework or the student’s research. A brief report on the project must be produced and approved by the PHDC.
Approved Course List: The list of approved courses will be reviewed regularly by the PHDC and is subject to change. Any changes must be approved by the CSE Department. In order for a course to be considered for inclusion in the list, the course must be rigorous and the students in it must be evaluated individually. Examples of inappropriate courses include those in which students are traditionally not differentially evaluated (e.g., all students receive A’s or “pass”) and courses in which grades are based on attendance or making a presentation of someone else’s work, rather than on tests and assignments.
Students, under their advisors’ guidance, should select their courses from the approved list so that they are exposed to a broad set of topics in computer science.
(b) Free choice courses: Students must take 2 free choice courses in addition to the 4 required courses from the approved list. Students can use any graduate course at NYU as free choice courses, but must obtain advisor approval to use a course not on the approved list. Students cannot use independent study courses (such as Advanced Project CS-GY 9963 or Readings in Computer Science, CS-GY 9413 and CS-GY 9423) or dissertation. No exemptions are available for free choice courses.
(c) GPA requirement: Students must receive a grade of at least B in each of the six courses used to fulfill the breadth requirement. The average in the 4 approved list courses used to fulfill the breadth requirement must be at least 3.5. (For students who receive exemptions allowing them to take fewer than 4 approved list courses, the average will be calculated over those courses.) The average in the 2 free choice courses must also be at least 3.5.
(d) Requirement for Students who have never taken an Algorithms Course: Any student who has not taken a course in Algorithms prior to entering the PhD program, at either the undergraduate or the graduate level, must take a graduate course in algorithms while in the PhD program. Students may take CS-GY 6033 (Design and Analysis of Algorithms I), CS-GY 6043 (Design and Analysis of Algorithms II), or CSCI-GA.3520 (Honors Analysis of Algorithms) to fulfill this requirement. The department may revise this list in the future depending on course offerings. Alternatively, students may petition the PHDC to use another course. The grade received in the course must be at least B.
Certification of Completion of Breadth Requirement
Once a student has fulfilled the breadth requirements, the student must fill out a Completion of Breadth Requirement form, listing the 6 courses taken to fulfill the requirement and specifying which ones are being used to meet the Theory requirement and the Systems & Applications requirement. Documentation for exemptions, if any, must be included. The student’s advisor will verify that the breadth requirement rules were followed before signing the form. It is the student’s responsibility to submit a Completion of Breadth Requirement form, with documentation of any exemptions, to the PHDC chair or designated assistant by the beginning of the semester that follows the student’s completion of the breadth requirement.
4. Depth Requirement
By the end of a student’s third semester in the program, at the latest, the student must be involved in a research project under the guidance of a faculty research advisor. It is the responsibility of each student to find a faculty advisor and a research project, and to inform the PHDC Chair about his/her choice of advisor. Students must inform the PHDC chair if they change their research advisor.
To satisfy the depth requirement, students must take a qualifying exam (QE) based on their research. The QE must be taken before the start of the student’s fifth semester in the program. Students are required to form a QE committee, select an exam topic, and a tentative date approved by the advisor and committee, by the end of their third semester.
The QE committee must consist of the advisor and at least two other members. The committee must be approved by the advisor and the PHDC. The advisor is the designated chair of the committee. All members of the QE committee must be CSE faculty, faculty from other departments at NYU, or individuals of like standing from outside the university. At least two of the QE committee members must be tenured or tenure-track members of the CSE department, unless permission is obtained from the PHDC to include only one such member.
For the QE, the student must give an oral presentation of her/his research accomplishments to the QE committee and write a detailed document describing those accomplishments. The document must be submitted to the QE committee and the PHDC no later than one week before the oral presentation. A student is expected to have conducted original research by the time of the exam. This research may have been carried out independently or in collaboration with faculty, research staff, or other students. Students are encouraged, but not required, to have publication-worthy results by the time of the exam. It is not sufficient for a student to present a survey of previous work in an area or a reimplementation of algorithms, techniques, or systems developed by others.
The committee, by majority vote, gives a grade for the exam as one of “PhD Pass”, “MS Pass”, or “Fail.” The chair of the QE committee will send this grade in writing to the student and to the PHDC chair, together with a written evaluation of the student’s performance, approved by the QE committee members. A student who does not receive a “PhD pass” may request permission from the PHDC to retake the exam. The PHDC will consult with the QE committee, review the case and make the final decision as to whether a retake is allowed or not. A student may petition the PHDC to change one or more members of the QE committee, but approval of the request will be at the PHDC’s discretion.
If the request for a retake is approved, the QE committee will determine the date for the second attempt. If the student is not allowed to retake the exam, the student will not be allowed to continue in the PhD program in the following semester. If the student does not pass the qualifying exam on the second attempt, or otherwise does not satisfy the conditions given to her/him upon failing the exam the first time, the student will not be allowed to continue in the PhD program in the following semester.
Students that receive a “PhD Pass” or “MS Pass” have the option to obtain an MS degree.
To receive an MS degree in the course of PhD studies, a student must:.
- Complete 30 credit hours at NYU not used toward any other degree. A GPA of 3.0 or better must be achieved.
- Satisfy the breadth requirement described above.
- Receive either an MS or PhD pass on the QE.
- Students may earn no more than a combined total of 9 credits of project, guided studies, readings, or thesis toward fulfillment of the MS degree requirements.
If a student has passed the QE and then changes his/her area of research, the student need not retake the QE.
Part-time students can petition the PHDC for extensions to the deadlines associated with the qualifying exam. Extensions should be for at most 2 semesters, except in extraordinary cases. Approval of extensions is at the discretion of the PHDC.
5. Thesis Proposal and Presentation
Within 6 months of passing the QE, each student is required to form a dissertation guidance committee. This committee must be approved by the student’s research advisor and by the PHDC. The committee must include at least four members. The committee members can be CSE faculty, faculty from other departments at NYU, or individuals of like standing from outside the university. At least one member of the dissertation guidance committee must be a tenured or tenure-track CSE faculty member, and at least one member of the committee must be from outside the CSE department.
By the end of the student’s fifth semester in the program, the student and committee must set a tentative date for the thesis proposal presentation. The presentation must be done prior to the start of the student’s seventh semester in the program.
Before finalizing the date of the presentation, the student must submit a written thesis proposal to the dissertation guidance committee which should include:
- a description of the research topic
- an explanation of how the research will advance the state of the art, and
- a tentative research plan
After the dissertation guidance committee has approved the thesis proposal, the student should schedule the thesis proposal presentation and notify the PHDC chair once this has been finalized. The presentation should be announced to the faculty by the PHDC chair at least one week before it occurs. The presentation is open to all faculty. It may also be open to others at the discretion of the research advisor.
Substantial subsequent changes to the thesis topic must be approved by the dissertation guidance committee.
6. Thesis and Thesis Defense
The last, and most substantial, aspect of the PhD program is the dissertation. The research for the dissertation should be conducted in close consultation with the research advisor. When the adviser determines that the student is ready to defend the thesis, a dissertation defense will be scheduled. For the defense, the student will give an oral presentation describing the thesis research, which is open to the public. Following the oral presentation and an initial question and answer session, the dissertation committee and CSE faculty may ask the student further questions in closed session.
Other requirements for the PhD dissertation and defense can be obtained from the Office of the Associate Dean for Graduate Academics in the NYU Tandon School of Engineering.
7. Annual PhD Student Assessment Meeting
All Ph.D. students will be formally reviewed each year in a PhD Student Assessment Meeting. The review is conducted by the entire CSE faculty and includes at least the following items (in no particular order):
- All courses taken, grades received, and GPAs.
- Research productivity: publications, talks, software, systems, etc.
- Faculty input, especially from advisors and committee members.
- Student’s own input.
- Cumulative history of the student’s progress.
As a result of the review, each student will be placed in one of the following two categories, by vote of the faculty:
- In Good Standing: The student has performed well in the previous semester and may continue in the Ph.D. program for one more year, assuming satisfactory academic progress is maintained.
- Not in Good Standing: The student has not performed sufficiently well in the previous year. The consequences of not being in good standing will vary, and may include being placed on probation, losing RA/GA/TA funding, or not being allowed to continue in the PhD program.
Following the review, students will receive formal letters which will inform them of their standing. The letters may also make specific recommendations to the student as to what will be expected of them in the following year. A copy of each student’s letter will be placed in the student’s file.
8. NYU Tandon School of Engineering Requirements
Other requirements can be found in the NYU Tandon School of Engineering Bulletin. Students must meet all applicable requirements, including graduate study duration, credit points, GPA, and time-to-degree requirements.
The following courses at NYU Tandon of Engineering can be used to satisfy the breadth requirements:
- CSCI-GA 3520 Honors Analysis of Algorithms
Systems & Applications
- CSCI-GA.2243 High Performance Computer Architecture
- CSCI-GA.2620 Networks and Distributed Systems
- CSCI-GA.3110 Honors Programming Languages
- CSCI-GA.3130 Honors Compilers
- CSCI-GA.3250 Honors Operating Systems
- CSCI-GA.2270 Computer Graphics
- CSCI-GA.2271 Computer Vision
- CSCI-GA.2434 Advanced Database Systems
- CSCI-GA.2560 Artificial Intelligence
- CSCI-GA.2565 Machine Learning
- CSCI-GA.2566 Foundations of Machine Learning
- CSCI-GA.2590 Natural Language Processing