These requirements were approved at the faculty meeting on September 12, 2002.
Students admitted in fall 2002 and later are expected to follow the requirements listed below.
To receive a PhD in Computer Science at NYU, a student must:
- satisfy a breadth requirement, intended to ensure overall
knowledge of computer science,
- satisfy a depth requirement, which has two purposes: testing
the knowledge of the student's chosen research area and ensuring 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 thesis committee,
and present an oral thesis defense,
- satisfy graduate study duration, credit points, GPA and time to degree requirements.
1. Breadth requirements
for breadth requirement form.
Rationale: The breadth requirement is designed to ensure competence
across three broad areas of computer science: theory, systems, and
applications. Within theory, the topic of algorithms is a requirement
for every student.
Every student must complete requirements (1a), (1b), (1c), and (1d)
by May 15 of the second year of PhD study in order for support to be
Every student must receive a grade of A or A- on the final
examination in the Honors Algorithms course. Students may
take the final exam without being enrolled in the course.
The syllabus and final exam for every offering of the Honors
Algorithms course will be determined by a committee of faculty
members who routinely teach this class.
This requirement can be satisfied in two ways. Either:
- the student receives an A or A- in an approved
course in systems listed in Appendix.
- the student has received an A or A- in a similar PhD-level
systems course at another university with standards comparable
to NYU's. This determination will be made by the Director of
Graduate Studies (DGS). In this case, the student is required
to 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 accepted by the DGS.
This requirements is satisfied in one of three ways. Either:
the student receives an A or A- in an approved applications course
listed in Appendix,
- the student passes a departmental exam in one of the subjects, if
an exam is offered, or
the student has received an A or A- in a similar PhD-level
applications course at another university with standards comparable
to NYU's. This determination will be made by the DGS.
(1d) Free choice
The student must either:
- receive an A or A- in an approved course in theory listed in Appendix.
- receive an A or A- in an additional course from the courses that
can be used to satisfy requirements (1b) or (1c). This course
cannot coincide with the courses used to satisfy (1b) and (1c) or
have received an A or A- in a similar PhD-level
course at another university with standards comparable
to NYU's, substantially different from the courses used to satisfy
requirements 1b and 1c. This determination will be made by the DGS.
Once a student has passed all courses and exams necessary to satisfy the
breadth requirement, the student must inform his or her academic advisor
in writing, specifying how each of parts 1a, 1b, 1c, and 1d has been satisfied.
The academic advisor verifies that the breadth requirement rules were
followed and forwards the information to the DGS.
The classes that can be used to satisfy breadth requirements
will be reviewed regularly by the graduate curriculum committee;
The graduate curriculum committee proposes the changes to the faculty for approval.
Current list of approved classes can be found in the appendix.
The following standards will be maintained:
(a) Classes must be at the PhD level, i.e., more advanced
than undergraduate or MS-level classes.
(b) The classes and exams must be rigorous and stable. Examples of
inappropriate classes include those in which students
are traditionally not differentially evaluated (e.g., all students receive As
or "pass"), courses whose content completely changes from year
to year, and courses in which grades are based on attendance or making
a presentation of someone else's paper, rather than on tests and
(c) Acceptable systems classes will involve substantial software
2. Depth requirement
for depth requirement forms.
No later than May 15 of the second year of PhD study, each 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
DGS about his/her choice of advisor.
Students must inform the DGS if they change the research advisor.
Students are required to form a depth exam committee and have the
committee, an exam topic and a tentative date approved by the Director
of Graduate Studies by the end of the first semester of their second
year of studies, This exam may be taken no more than twice.
A DQE is administered by a committee of at least three faculty
members, nominated by the student and his/her research advisor,
and approved by the DGS. Each DQE will have a designated chair
who is not the student's research advisor.
If the research advisor is not a member of the committee,
the research advisor must write a letter evaluating
student's progress, and send it to the DQE committee members
before the exam.
The DQE committee will define a syllabus, which must be approved
by the DGS, and make the syllabus available to the student
no later than two weeks before the exam.
The DQE has two parts:
(2a) An examination to demonstrate the student's knowledge
of the research area. The scope of this exam should be similar
to a typical PhD-level special topics course. It should not be
as broad as an introductory course nor as narrow as a thesis.
Examples of suitable topics are "Type theory in programming languages",
"Probabilistic algorithms", "Computational learning theory", "3-D modeling",
"Semidefinite programming", and "Low-power computing". Topics such
as "Databases" or "Programming languages" would be too broad;
topics such as "Voronoi diagrams" or "Tail-recursion optimization"
would be too narrow.
This exam may be oral or written, at the discretion of the
committee. The requirement is that it seriously test the
student's knowledge of a research area as distinct from the
student's research accomplishments.
(2b) An oral presentation of the student's research
accomplishments. A student is expected to have conducted
original research by the time of the exam.
This research may have 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 separate grade for (2a) and
(2b) as one of "PhD Pass", "MS Pass", or "Fail." A PhD pass on both
parts must be achieved for support to be continued beyond the second
year. A student who receives a "PhD Pass" on only one part of
the exam may request permission from the committee to retake only the
other part of the exam.
To receive an MS degree in the course of PhD studies a student must:
- Complete 36 credit hours at NYU not used toward any other degree.
At least 28 credit hours must be taken within the Graduate School of
Arts and Sciences (GSAS) and a GPA of 3.3 or better must be achieved.
Satisfy the breadth requirement described above.
Receive either an MS or PhD pass on each part of the DQE.
If a student has passed the DQE and then changes his/her area of research,
the student need not retake the DQE.
3. Thesis proposal and presentation
Students are required to form a thesis proposal committee and have the
committee and a tentative date for the thesis proposal presentation approved by
the Chair and the Director of Graduate Studies by the end of the first semester
of their third year of studies.
When a student is ready to start work on the PhD thesis, the student
must (i) select, with the approval of
his/her research advisor and the DGS, a thesis reading
committee, and (ii) submit a written thesis proposal to the
The student and the student's research advisor suggest the composition
of the thesis reading committee for approval by the DGS and Department Chair.
The committee must include at least three members.
All changes to the composition of the committee must be approved by the DGS and the Chair.
The committee members can be regular computer science faculty, faculty from other
departments, or individuals of like standing from outside the University.
At least one member of the reading committee must be regular Computer Science
The thesis proposal 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 thesis reading committee has approved the thesis proposal,
the student should schedule a thesis proposal presentation and notify the Program
Adminisitrator once this has been finalized. This presentation should be announced
to the faculty by the Program Administrator,PhD Program, at least one week before
it occurs. The presentation may or may not be open to people other than
faculty, at the discretion of the research advisor.
Substantial subsequent changes to the thesis topic must be
approved by the thesis reading committee. The proposal must be defended
no later than May 15 of the third year of studies.
4. Thesis and thesis defense
The final step in the PhD program is the student's defense of
his/her PhD thesis.
The procedures to be followed for the
thesis defense can be found on the
Dissertation Defense Checklist.
5. Other requirements
Students must end the semester in which they take their fifth class
and all subsequent semesters with a GPA of 3.5 or higher.
Note that the departmental requirement in this
case is more stringent than the GSAS requirement (cumulative GPA of at
In addition the following general GSAS requirements have to be
- Students must complete three years of full-time study beyond the
undergraduate degree, at least one year of which must be in residence
at the GSAS.
Students must complete 72 points of graduate credit including at least 32
points for courses taken at the GSAS. At any time, students must have
successfully completed 66 percent of credits attempted while at NYU, not
including the current semester. Courses with grades of I, W, and F are not
considered successfully completed.
- Time Limit. All requirements for the doctoral degree must be
completed no later than ten years from the initial date of matriculation.
However, if the student transfers
credit from classes taken as part of a previously earned master's
degree, then the time limit is seven years.
Other GSAS and NYU requirements can be found in the GSAS Bulletin.
6. Academic standing
To be in good academic standing
a student must meet the deadlines for all requirements specified in this
document and maintain the required minimal GPA.
For supported students, maintaining good academic standing
is a condition of the guaranteed support. If a student fails to
maintain good academic standing, his or her support may be
discontinued, and the
student may be removed from the program. A student's
academic standing is determined by the DGS each semester. The PhD
admissions and financial aid committee decides in which cases support
is discontinued. In most cases, a student will be removed from the program
when his or her support is
discontinued for failure to maintain good academic standing.
The following courses can be used to satisfy the breadth requirements:
- CSCI-GA.3520 Honors Analysis of Algorithms.
- CSCI-GA.2243 High Performance Computer Architecture,
- CSCI-GA.2620 Networks and Distributed Systems.
- CSCI-GA 3033 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 2567 Machine Learning and Computational Statistics*,
- CSCI-GA.2572 Deep Learning*,
- CSCI-GA.2590 Natural Language Processing,
(*Please note: Only one of these classes can be counted for breadth
requirements (either Applications or Free Choice). Machine Learning
emphasizes applications, and Foundations of Machine Learning emphasizes
theoretical aspects of machine learning, although both include
theoretical and practical components. Please familiarize yourself with
class requirements and consult your academic advisor before choosing one
of these classes.)
1d. Free choice
Any of the courses listed under 1b and 1c, or any of the following
- CSCI-GA.2390 Logic in Computer Science,
- CSCI-GA.2420 Numerical Methods I.
- CSCI-GA.2421 Numerical Methods II,
- CSCI-GA.2945 Numerical Optimization,
- CSCI-GA.3130 Honors Theory.
- CSCI-GA.3210 Introduction to Cryptography.
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