PhD

Information Systems and Technology

Students work with Huaxia Rui, Professor

Effective solutions for complex business problems.

Simon’s PhD in Information Systems and Technology focuses on the business aspects of Information Technology use and management, and the analytic and quantitative tools and techniques to address them. The research conducted by the students and faculty has significantly advanced the state of the art in research on information systems in general, with an emphasis on information systems economics and machine learning modeling.

Prepare with Math Camp.

Program Outline: Information Systems and Technology

The First Year

The first year provides students with a strong methodological foundation in order to prepare them for research in the advanced years of the program. Students are required to take courses offered by Simon Business School as well as the University of Rochester. First year students are required to pass Preliminary Requirements by demonstrating proficiency in specific courses. A research-oriented first-year paper is due August 31 of the start of the second year.

The Second Year

The second year deepens students' knowledge of Information Systems. Students work in conjunction with the faculty to write two papers on two individual research topics. These papers are due by May 31 of the second year. Students are also required to write a Qualifying Exam paper, due by November 30 of the third year. This paper is usually a more in-depth version of one of the two papers used for the second-year papers requirement.

The Third Year and Beyond

Students will take additional courses in the third year after passing the Qualifying Exam. Students also begin work on a dissertation. Research in the field of Information Systems and Technology focuses on problems of design, performance analysis, and optimization of information systems.

Thesis and Proposal

Students are expected to submit a Thesis proposal paper along with a faculty advisor and committee that has agreed to serve on the dissertation committee. The dissertation must be an original critical or synthetic treatment of a suitable subject, an original contribution to creative art, or a report on independent research formulated in a manner worthy of publication. The exact form and timing of this proposal is defined by the area requirements.

Advancement to Candidacy

This is achieved after passing the Preliminary and Qualifying Exams. At the conclusion of the qualifying exam, the faculty administering the qualifying exam evaluate the student and through that evaluation make a recommendation to the PhD Faculty Director and Senior Associate Dean of Faculty that the student advance to candidacy.

 

Simon Students Congregate in the Quad

Required Courses.

The Course Catalog contains degree requirements and course descriptions. Please refer the Simon Registrar's website for the current Course Catalog.

 

PhD Information Systems and Technology Courses

CIS 511

Research Topics and Methods in Information Systems

CIS 511

3 credits

This course introduces important research methods/topics for IS researchers, covering analytical modeling, causal inference, and machine learning. For analytical modeling, we will discuss auction and mechanism design for information/ computation goods. For causal inference, we will establish the probabilistic foundation of commonly used methods such as DID, matching, IV, and regression discontinuity. For machine learning, we will introduce the statistical learning theory, SVM, EM, MCMC, variational inference, and deep learning.

MSM 511

Advanced topics in IS and OM

MSM 511

3 credits

This course introduces students to research in Information Systems (IS) and Operations Management (OM). Multiple lectures will be dedicated to each topic, covering the necessary mathematical background, primary analysis techniques, and important, seminal, or recent papers within each area. The course aims to attain the following objectives: learn about what constitutes research in IS and OM, develop critical thinking about academic papers, familiarize students with new research areas, provide opportunity to think about new research problems, and practice constructing and delivering academic talks.