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Programme Structure & Curriculum

Our Value Proposition

Our PhD programme is distinctive in its emphasis on the following:

INTER-DISCIPLINARY WORK

Our PhD students are trained to work across research areas. The curriculum covers three blocks that have high market demands - Artificial Intelligence & Data Science, Human-Machine Collaborative Systems, and Information Systems & Technology.

The PhD programme aims to train students to work at the intersection of IT and business, specifically,

  • Research on deep technology challenges in real computing systems that impact society or business.
  • Research on tools and methodologies to translate societal challenges or business goals into technology solutions.

APPLIED RESEARCH

Students to work with industry datasets and commercial platforms. Students will learn to conduct their research in the context of real information systems and business goals.

The PhD theses will emphasize solving real-world problems and building usable technology solutions, rather than working only on component technologies. Selected students will also get to participate in industry projects, and experiment with real data sets on commercial test-beds to provide industry relevance to the students' research. This aspect of the PhD training is critical to grooming promising students for good job openings, rather than leaving placement till near the students' graduation.

INDUSTRY-RELEVANT TRAINING

Our PhD students will acquire professional skills that are important in industrial R&D, such as competitive intelligence & intellectual property management. Students will have opportunities to network with academic researchers and industry practitioners.

To achieve our focus of applied research at the intersection of IT and business, the curriculum provides:

  • Depth in the primary area to which a candidate's thesis belongs.
  • Breadth in IT and management.
  • Professional skills like research methodology, and competitive intelligence & intellectual property management.

3rd and 4th year PhD students will co-teach classes with experienced professors, and also mentor fresh PhD students.

 
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Curriculum Composition

This is a direct PhD programme, with a maximum candidature period of five (5) years and a minimum period of three (3) years for full-time students.

Our PhD students should identify a (preliminary) research area at the time of admission, so that they can begin research exploration right from the first year of candidature.

Graduate coursework : In the first two years of study, students will enroll in intensive courses to build their research depth and breadth, as well as professional skills:

Depth Requirements

Students will enroll in the courses in the primary area, and undertake research apprenticeship with their primary advisors. Each PhD course covers important research papers on key topics and techniques that students need to be acquainted with in order to carry out research in an area.

Breadth Requirements

Students will attend courses in Artificial Intelligence & Data Science, Human-Machine Collaborative Systems, and Information Systems & Technology. The breadth requirements are intended to help the PhD students establish their contact networks and to expose them to industry practices.

Professional Skills

To round up the PhD training, the curriculum includes workshops on English Communications; Scientific Writing and Presentation; Institutional Review Board (IRB) training, and teaching skills.

Curriculum Requirements

TOTAL 40 COURSE UNITS (CUs)

COURSEWORK (6 CUs)

  • PhD in Information Systems Students
    • IS713 +
    • ECON601 or ECON611 or ECON681 +
    • 1 SCIS PhD Courses +
    • 3 courses offered by any SMU Doctoral Programmes
  • PhD in Computer Science Students
    • 2 courses from own research area +
    • 4 SCIS PhD Courses

EMPIRICAL RESEARCH PROJECTS - ERPs (4 CUs)

  • 3 CUs of term papers/projects in the primary area
  • 1 CU of term paper/project in another area OR 1 course offered by any SMU Doctoral Programmes

ADVANCED RESEARCH TOPICS - ARTs (2 CUs)

  • Information Systems Topics (0.5CU each term for 2 terms)
  • Information Systems Seminars (0.5 CU each term for 2 terms)

DISSERTATION (28 CUs)

Programme Schedule

The following tables give a model programme schedule for a full-time PhD candidate.

There is some degree of flexibility for individual students to encourage innovation in both instructions and research.

Year 1

Term 1

  • 3 courses (1 CU each)
  • 0.5 ART (IS Topics)

Term 2

  • 3 courses (1 CU each)
  • 0.5 ART (IS Topics)

Term 3

  • 1 ERP (1 CU each)
  • Prepare for Qualifying Exam

Year 2

Term 1

  • 1 ERP (1 CU each)
  • Pass Qualifying Exam

Term 2

  • Prepare Dissertation Proposal

Term 3

  • Prepare Dissertation Proposal

Year 3

Term 1

  • 1 ERP (1 CU each)
  • 0.5 ART (IS Seminars)
  • Prepare Dissertation Proposal

Term 2

  • 0.5 ART (IS Seminars)
  • Prepare Dissertation Proposal

Term 3

  • Submit Dissertation Proposal Report
  • Oral defense of Dissertation Proposal
  • Conduct Dissertation Research

Year 4

Term 1

  • 1 ERP (1 CU each)
  • Conduct Dissertation Research

Term 2

  • Conduct Dissertation Research
  • Submit Dissertation Report
  • Oral defense of Dissertation

Term 3

  • Revise Dissertation Report
  • Submit Approved Dissertation Report to PGR Office

YEAR 1 : PREPARATION PHASE

  • A student begins by doing apprenticeship in a chosen research area with an assigned advisor.
  • The first semester is spent on literature survey and identifying potential thesis topics, and attending breadth courses.
  • By the end of the first semester, the student should choose two areas to focus in, one of which becomes the depth area and the other the breadth area.
  • In the second semester, the student attends advanced courses in the depth and breadth areas.
  • By the end of the second semester, the student should have delivered survey/research papers and/or grant proposals.
  • The advanced courses and research apprenticeship are graded to ensure that students do not neglect research while doing coursework in the first year of candidature.
  • The PhD programme committee will evaluate the student's readiness to enter into the next phase based on his/her course grades, as well as papers from the Research Apprenticeship.

YEAR 2 - 4 : RESEARCH PHASE

The student is expected to form a 4-member dissertation committee, and pass an oral qualifying examination followed by a dissertation proposal within the second year of candidature.

  • The dissertation proposal should outline the research scope and present initial results.
  • To ensure that the dissertation has sufficient depth, yet address the intersection of IT and business, the student is encouraged to identify a primary advisor in his/her depth area, and a secondary advisor in the breadth area.
  • Moreover, the dissertation committee should have representation from different research areas, as well as a mix of tenure-track and practice-track professors.
  • The PhD programme committee conducts half-yearly progress review of all PhD students, and may arrange additional guidance for students where necessary.

YEAR 4 : DISSERTATION EXAMINATION

  • The student should arrange a final defense to an expanded, 4-member dissertation committee before the end of the fourth year.
  • The dissertation committee should include an external examiner.

Last updated on 06 Jul 2021 .