Program Overview

PH.D. Program in Computer Science at NYU

The PhD program in Computer Science at New York University is designed to provide students with a comprehensive education in the field of computer science. The program is structured to ensure that students gain a broad understanding of computer science, as well as specialized knowledge in their area of research.

Program Requirements

To receive a PhD in Computer Science at NYU, a student must satisfy the following requirements:

• Satisfy a breadth requirement
• Satisfy a depth requirement
• Satisfy a teaching requirement
• Write and defend a thesis proposal
• Write and defend a PhD thesis
• Satisfy general NYU degree requirements

Breadth Requirements

The breadth requirement is designed to ensure competence across three broad areas of computer science: theory, systems, and applications. The requirements are as follows:

1. Algorithms: Every student must receive a grade of A or A- on the final examination in the Honors Algorithms course.
2. Systems: This requirement can be satisfied in two ways:

• The student receives an A or A- in an approved course in systems.
• The student has received an A or A- in a similar PhD-level systems course at another university with standards comparable to NYU's.

3. Applications: This requirement is satisfied in one of three ways:

• The student receives an A or A- in an approved applications course.
• The student passes a departmental exam in one of the subjects.
• The student has received an A or A- in a similar PhD-level applications course at another university with standards comparable to NYU's.

4. Free Choice: The student must either:

• Receive an A or A- in an approved course in theory.
• Receive an A or A- in an additional course from the courses that can be used to satisfy requirements (1b) or (1c).

Depth Requirement

The depth requirement forms are available on the forms page for PhD students. 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.

Teaching Requirement

By the end of the third year of study, each student must have served as a section leader of at least one course in the department. Courses on related topics outside the department may also be used to satisfy this requirement, subject to approval by the Director of Graduate Studies.

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.

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.

General NYU 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. In addition, the following general GSAS requirements have to be satisfied:

1. 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.
2. Students must complete 72 points of graduate credit, including at least 32 points for courses taken at the GSAS.
3. Time Limit: All requirements for the doctoral degree must be completed no later than ten years from the initial date of matriculation.

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.

Appendix

The following courses can be used to satisfy the breadth requirements:

1. Algorithms:

• CSCI-GA.3520 Honors Analysis of Algorithms

2. Systems:

• CSCI-GA.2243 High Performance Computer Architecture
• CSCI-GA.2434 Advanced Database Systems
• CSCI-GA.2620 Networks and Mobile Systems
• CSCI-GA.2621 Distributed Systems
• CSCI-GA.3110 Honors Programming Languages
• CSCI-GA.3130 Honors Compilers
• CSCI-GA.3140 Abstract Interpretation
• CSCI-GA.3250 Honors Operating Systems

3. Applications:

• CSCI-GA.2270 Computer Graphics
• CSCI-GA.2271 Computer Vision
• 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

4. Free Choice:

• Any of the courses listed under Systems and Applications, or any of the following courses:
  • 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.2945 Convex and Non-Smooth Optimization
  • CSCI-GA.3210 Introduction to Cryptography
  • CSCI-GA.3350 Honors Theory of Computation