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Doctoral Program in Information Systems

 


Overview of the IS Doctoral Program

Mission:
To educate and train scholars who will produce first-rate IS research and who will succeed as faculty members in first-rate universities. We offer tracks in technical perspectives on IS, economic perspectives on IS, and organizational/management perspectives on IS.

Admissions and performance:
We enroll an average of three students each year out of more than 100 highly qualified applicants. Students enrolling typically have GMATS over 700 or GREs over 1400. International students typically have TOEFLs higher than 640. Our students are highly competitive within Stern and nationally. Recently our students have received school-wide awards as "outstanding doctoral students." They have won acceptance at doctoral consortia sponsored by the Academy of Management and the International Conference on Information Systems. And they have won national dissertation research competitions.

Advising and evaluation:
The IS doctoral program faculty director advises all first-year doctoral students. During the first year students have many opportunities to get to know the research interests of all departmental faculty. By the beginning of the second year, students have selected a concentration advisor who will guide them through the comprehensive exam process and up to the thesis stage. By the middle of the third year students will have selected a thesis advisor. Each year every student submits a statement of intellectual progress to his/her advisor. All faculty meet to review the progress of all students in a day-long meeting each year. At this time, the student's intellectual progress is reviewed and plans for the following year are considered. The results of this review include a formal letter to the student assessing the previous year's work and offering guidance for the following year's work. All students take a comprehensive written and oral exam at the end of the second year. Students defend their thesis proposal by March of their fourth year and defend their completed dissertation at the end of the fourth year or during the fifth year.

Research and interaction with faculty:
The heart of the IS doctoral program is immersion in a community of researchers. Every student has a formal research apprenticeship with one or more faculty members each year. Every student participates in formal and informal research seminars each week with departmental faculty and visitors. Every student presents research in progress and works toward producing publishable papers, usually with a faculty co-author. Students learn to be researchers by doing research. They learn to be research colleagues by working with others and critiquing their research.

Placement record:
In the past ten years, our graduates have accepted faculty positions at such schools as University of California at Berkeley, Hong Kong University of Science & Technology, University of Maryland, University of Minnesota, University of Texas at Austin, the University of British Columbia, National University of Singapore, The Wharton School and the University of Cambridge, UK.
 
Please click on the links on the right to learn how to apply, to attend an information session, and to contact the Stern School Doctoral Office. 

Arun Sundararajan
Coordinator, Information Systems Doctoral Program
IOMS Department

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Program Requirements

All students take a common core of courses during their first year which provides an overview of the major research areas in IS and the fundamental knowledge necessary for specialized course work in the second year. In the second year students take specialized course work in one of three concentrations: technical perspectives, economic perspectives, behavioral/managerial perspectives.
 

YEAR ONE

Mandatory Breadth Courses (3)

  • Behavioral Research Methods
  • Micro-economics
  • Technical Foundations
Probability & Statistics (2)
  • Each student is required to take 1 Probability and 1 Statistics course, from a list of approved courses.
IS Dept Core Research Courses (3)
  • Technical Research in IS
  • Economics Research in IS
  • Behavioral/Managerial Research in IS

Research Apprenticeship

YEAR TWO - Each student chooses one concentration track

Technical Track:

  • A programming requirement, may be satisfied in a variety of ways
  • Honors Analysis of Algorithms
  • Artificial Intelligence
  • Optimization
  • Database Systems
  • Machine Learning/Data Mining
  • Other courses based on student's interest
  • Research apprenticeship

Economics Track:

  • Mathematical Methods for Economists
  • Econometrics
  • Game Theory
  • Students will take elective courses in the Stern Economics Department, at the Graduate School of Arts and Sciences, in Operations Management, Statistics, or at Courant as specified in consultation with the advisor
  • Research apprenticeship

Behavioral/Managerial Track:

  • Any two of the following four Stern Management Department Courses
  • Organizational Behavior
  • Managerial Cognition
  • Organizational Theory
  • Strategy
  • At least one research methods or statistics course beyond the first year courses.
  • Students may take doctoral level courses in Psychology, Sociology, Political Science, Public Policy, History, Education, or Law.
  • Electives in the area of interest
  • Research Apprenticeship

YEAR THREE

  • Thesis research
  • Research apprenticeship
  • Teaching apprenticeship (in year 3 or 4)
  • Teaching one course (in year 3 or 4)

YEAR FOUR

  • Thesis research
  • Research apprenticeship
  • Teaching apprenticeship (in year 3 or 4)
  • Teaching one course (in year 3 or 4)

YEAR FIVE

  • Thesis research
  • Research apprenticeship

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Doctoral Courses

  • INFO-GB.3345 (B20.3345)  Doctoral Seminar in Digital Economics  (offered in Spr 2012)
    This course introduces students to scientific paradigms and research perspectives related to the economics of information technologies. Topics in 2012 include information goods, piracy, digital rights management, network economics, sponsored search auctions, user-generated content, contagion in networks, technological innovation, IT productivity, the digital commons and online privacy.  
  • INFO-GB.3382 (B20.3382)  Research Seminar on IT and Organizations: Social Perspectives (offered in Spr 2012)
    The course introduces students to sociological and organizational literature on the role of Information Technology in organizations and society.
     
  • INFO-GB.3383 (B20.3383)  Networks, Crowds & Markets 
     
  • INFO-GB.3386 (B20.3386)  Technical Foundations of IS
     
  • INFO-GB.3355 (B20.3355)  Behavioral Research Methods
     
  • INFO-GB.3391 (B20.3391)  Research Seminar in Data Science  (offered in Spr 2012)
    In this course we will take a deep dive into selected topics in data science. The focus will be two-fold. First, we will read textbook segments, classic papers, and new research, with the goal of understanding research in data science. Second, we will study the actual practical application of data science methods to extract knowledge from large-scale data. We will cover topics such as machine learning, data mining, information retrieval, text classification, sentiment analysis, similarity analysis, network analysis, graphical models, Bayesian models, topic models, model evaluation, crowd-sourcing and micro-outsourcing, massive-scale data processing, reducing data for analytic purposes, and more. The selection of which topics are covered in a particular semester will be based on: (i) the current research and business environments, (ii) the research interests of the IS faculty, and (iii) the interests of the students in that semester. We also will discuss applications that are of current interest, such as recommender systems, social-network marketing, online advertising, Mechanical Turking, and more.

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PhD Arun Sundararajan 170x240
Arun Sundararajan, Professor of IOMS

Questions about the PhD Program in Information Systems?

Contact: Arun Sundararajan
IS Program Coordinator
asundara@stern.nyu.edu

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