The primary requirement of the Ph.D. student is to do original and substantial research. This research is reported for review in the Ph.D. dissertation.
There are three milestones for a dissertation: 1) passing the qualifying exam; 2) writing and successfully defending a thesis proposal; 3) writing and successfully defending a thesis. Students are responsible for regularly viewing and understanding the processes and specific requirements for these milestones as detailed in the ML Ph.D. Handbook, as well as any additional requirements of their home unit.
Thesis advisors for the ML Ph.D. can be any of the participating ML Ph.D. Program Faculty, regardless of whether they are in the same unit as the student. Students will be eligible for Graduate Research Assistantships and Graduate Teaching Assistantships in accordance with the policies of their home units.
The purpose of the Qualifying Examination is to judge the candidate’s potential as an independent researcher.
The Ph.D. qualifying exam consists of a focused literature review that will take place over the course of one semester. At the beginning of the second semester of their second year, a qualifying committee consisting of three members of the ML Ph.D. Program Faculty will assign, in consultation with the student, a course of study consisting of influential papers, books, or other intellectual artifacts relevant to the student’s research interests. The student’s focus area and current research efforts (and related portfolio) will be considered in defining the course of study.
At the end of the semester, the student will submit a written report the demonstrates their understanding of both the technical content and the context of each artifact. Subsequently, the student will have a closed oral exam with the three members of the committee. The exam will be interactive, with the student and the committee discussing and criticizing each work and posing questions related to the student's current research to determine the breadth of the student’s knowledge in that specific area.
The success of the examination will be determined by the committee’s qualitative assessment of the student’s understanding of the theory, methods, and ultimate impact of the assigned syllabus.
The student will be given a passing grade for meeting the requirements of the committee in both the written and the oral part. Unsatisfactory performance on either part will require the student to redo the entire qualifying exam in the following semester. Each student will be allowed only two attempts at the exam.
Students are expected to perform the review by the end of their second year in the program. Students taking the qualifying exam should register for CS 7999. To receive a permit or if you have any questions about the qualifying exam, please contact the ML Academic Advisor, Stephanie Niebuhr at email@example.com.
As the first step towards completing a dissertation, the student must prepare and defend a Research Proposal. The purpose of the proposal is to give the faculty an opportunity to give feedback on the student’s research direction, and to make sure they are developing into able communicators.
The Ph.D. proposal consists of a short document - 30 pages or less - describing the student's thesis, and a presentation to a proposal committee consisting of three ML Ph.D. Program Faculty chosen by the student. All coursework must be completed before the proposal can be scheduled.*
The Ph.D. thesis committee consists of five faculty members, including the three ML Ph.D. Program Faculty who served on the proposal committee, and two additional members. At least one member must be external to the ML Ph.D. program. The committee is charged with approving the written dissertation and administering the final defense. The defense consists of a public seminar followed by oral examination from the thesis committee.
Institute guidelines and requirements for formatting the document can be found in the Georgia Institute of Technology Graduate Studies Thesis and Dissertation Manual.
*The Research Proposal and Ph.D. Thesis both require several forms before and after scheduling and moving forward with these milestones. Please review the ML Handbook and contact the ML Academic Advisor, Stephanie Niebuhr at firstname.lastname@example.org at least one month prior to express the intent of submitting your thesis proposal or defense, review coursework (due at the time of the proposal) and committee requirements, and clarify all details of the process.