Program Overview

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Information Systems (PhD)

The Information Systems (IS) field is a multidisciplinary area that is growing in importance as the information technology revolution transforms the scale of data, the nature of products, the organization of work, and the way people interact. The Stern IS department has played an active leadership role in defining the fields of data science and business analytics, engaging in cross-disciplinary scholarship in computer science, economics, machine learning, marketing, management science, and urban science.

Program Description

PhD students at Stern have the advantage of working with IS faculty who also maintain close research ties with the digital, banking, advertising, and media industries, which gives our students access to unique “big data” for research as well as opportunities for experiential learning.

Admissions

All applicants to the NYU Stern School of Business PhD Program are required to submit a complete application for admission. A complete application includes the online application, statement of purpose, optional essay, educational history and resume or CV, letters of recommendation, test scores, academic transcripts, and an application fee.

Program Requirements

The program requires the completion of at least 36-54 credits, and students may choose from one of three specializations as noted below.

Course List

• Major Requirements
  • ECON-GB 3351: Econometrics I (3 credits)
  • INTA-GB 4388: Behavioral Research Methods (3 credits)
  • ECON-GB 3335: Microeconomics: Theory and Applications (3 credits)
  • TECH-GB 3345: Doctoral Seminar in Digital Economics (3 credits)
  • TECH-GB 3382: Research Seminar on IT and Organizations: Social Perspectives (3 credits)
  • TECH-GB 3391: Research Seminar: Data Science (3 credits)
  • TECH-GB 3386: Technical Foundations of Information Systems (3 credits)
• Required Practica
  • TECH-GB 4101: Research Practicum-Inf Sy (1 credit)
  • TECH-GB 4102: Research Practicum II (1 credit)
  • TECH-GB 4103: Research Practicum-IS 3 (1 credit)
  • TECH-GB 4104: Research Practicum IV (1 credit)
  • TECH-GB 4105: Research Practicum-IS 5 (1 credit)
  • TECH-GB 4150: Teaching Practicum-IS (1 credit)
• Specialization Requirements
  • Students will select one of the following specializations: (9-13 credits)
    • Economics
    • Technical
    • Behavioral
• Electives
  • Other Elective Credits (0-14 credits)
• Total Credits (36-54 credits)

Curriculum Details

Although every doctoral student must satisfy general requirements, each student designs and completes an individual program of study.

Specialization Requirements

Economics

• Required Courses
  • APSTA-GE 2012: Causal Inference (3 credits)
  • DS-GA 1011: Fundamentals of Natural Language Processing (3 credits)
  • ECON-GB 3360: Topics in Economics: Industrial Organization (3 credits)
  • PHDC-GB 8683: (3 credits)
• Recommended Courses
  • MKTG-GB 4392: Quantitative Applications in Marketing II (3 credits)
  • MKTG-GB 4394: Advanced Empirical Methods (3 credits)

Technical

• Required Courses
  • APSTA-GE 2012: Causal Inference (3 credits)
  • CSCI-GA 3520: Honors Analysis of Algorithms (4 credits)
  • DS-GA 1005: Inference and Representation (3 credits)
  • DS-GA 1011: Fundamentals of Natural Language Processing (3 credits)
• Recommended Courses
  • CSCI-GA 3850: PhD Research Seminar (1 credit)
  • DS-GA 1002: Probability and Statistics for Data Science (3 credits)
  • DS-GA 1008: Deep Learning (3 credits)
  • DS-GA 3001: Special Topics in Data Science (3 credits)
  • INTA-GB 9912: Panel Data Analysis (Econometrics II) (3 credits)
  • MATH-GA 2830: Adv Tpcs in Applied Math (3 credits)
  • OPMG-GB 4333: Advanced Topics in Data-Driven Decision Making (3 credits)
  • STAT-GB 1304: (3 credits)
  • STAT-GB 3302: Statistical Inference and Regression Analysis (3 credits)

Behavioral

• Required Courses
  • MGMT-GB 3191: Profession Seminar (1.5 credits)
  • MGMT-GB 3381: Adv Resrch in Orgnz Behav (3 credits)
  • MGMT-GB 3387: Organization Theory (3 credits)
  • MGMT-GB 3191: Profession Seminar (1.5 credits)
• Recommended Courses
  • MGMT-GB 4301: Strategy (3 credits)
  • PHDC-GP 5905: (3 credits)
  • PHDC-GR 8405: (3 credits)
  • SOC-GA 2414: Sociology of Culture (4 credits)

Additional Program Requirements

Program of Study

Successfully complete a program of study, including completion of prerequisite coursework, basic research skills methodology courses, and major field of study and elective courses.

Comprehensive Examination

Successfully pass the comprehensive examination(s) required in the student’s area of study.

Teaching Workshop

Attend the Teaching Workshop and receive certification to teach an undergraduate course.

Teaching Preparations

Successful completion of the teaching practica as described in the PhD Handbook.

Teach an Undergraduate Course

Teach one undergraduate course or the equivalent during the 4th year of study.

Dissertation Proposal

Initiate a major piece of original research and present it for faculty approval.

Dissertation Defense

Complete a satisfactory dissertation and defend it successfully at the defense presentation. The research is the extension and completion of the research presented at the dissertation proposal.

Sample Plan of Study

• 1st Semester/Term
  • APSTA-GE 2012: Causal Inference (3 credits)
  • ECON-GB 3351: Econometrics I (3 credits)
  • INTA-GB 4388: Behavioral Research Methods (3 credits)
  • TECH-GB 4101: Research Practicum-Inf Sy (1 credit)
  • Total Credits: 10
• 2nd Semester/Term
  • DS-GA 3001: Special Topics in Data Science (3 credits)
  • INTA-GB 9912: Panel Data Analysis (Econometrics II) (3 credits)
  • TECH-GB 3382: Research Seminar on IT and Organizations: Social Perspectives (3 credits)
  • TECH-GB 3391: Research Seminar: Data Science (3 credits)
  • TECH-GB 4101: Research Practicum-Inf Sy (continued from Fall) (1 credit)
  • Total Credits: 12
• 3rd Semester/Term
  • DS-GA 1005: Inference and Representation (3 credits)
  • ECON-GB 3360: Topics in Economics: Industrial Organization (3 credits)
  • MKTG-GB 4391: Quantitative Applications in Marketing I (3 credits)
  • TECH-GB 3386: Technical Foundations of Information Systems (3 credits)
  • TECH-GB 4102: Research Practicum II (1 credit)
  • TECH-GB 4103: Research Practicum-IS 3 (1 credit)
  • Total Credits: 14
• 4th Semester/Term
  • TECH-GB 4102: Research Practicum II (continued from Fall) (1 credit)
  • TECH-GB 4103: Research Practicum-IS 3 (continued from Fall) (1 credit)
  • Electives (9 credits)
  • Total Credits: 9
• 5th Semester/Term
  • TECH-GB 4104: Research Practicum IV (1 credit)
  • TECH-GB 4150: Teaching Practicum-IS (1 credit)
  • Total Credits: 2
• 6th Semester/Term
  • TECH-GB 4104: Research Practicum IV (1 credit)
  • TECH-GB 4150: Teaching Practicum-IS (1 credit)
  • Total Credits: 2
• 7th Semester/Term
  • TECH-GB 4105: Research Practicum-IS 5 (1 credit)
  • Electives (4 credits)
  • Total Credits: 5
• Total Credits: 54

Learning Outcomes

Upon successful completion of the program, graduates will:

1. Acquire a broad working knowledge of their field of study.
2. Acquire advanced knowledge in a specific field of research.
3. Conduct independent research.
4. Be skilled presenters of academic research.
5. Be skilled teachers.

Policies

NYU Policies

University-wide policies can be found on the New York University Policy pages.

Stern Policies

Additional academic policies can be found on the Stern Graduate Academic Policies page.