Doctor of Philosophy in Artificial Intelligence and Data Science

The Doctor of Philosophy (Ph.D.) degree is a research-oriented degree requiring a minimum of 64 semester credit hours of approved courses and research beyond the Master of Science (M.S.) degree [96 credit hours beyond the Bachelor of Science (B.S.) degree]. The university places limitations on these credit hours in addition to the requirements of the Department of Civil Engineering.

A complete discussion of all university requirements is found in the current Texas A&M University Graduate Catalog.

NOTE: All documents requiring departmental signatures must be submitted to the Civil Engineering Graduate Office in DLEB 101 at least one day prior to the Office of Graduate Studies deadline.

Artificial Intelligence and Data Science Faculty Members

Admission
Admission to the AI/DS track is conditional upon meeting the general admission requirements. Also, students may only be admitted to the AI/DS track if a faculty member affiliated with the track is willing to supervise (and provide funding support via GAT or GAR or Fellowship) for the student. If a current student is approved to change from one track to another, they must complete the Track Change Request Form and send it to the CVEN Graduate Advising Office so notification can be sent to their original area coordinator. Please read the CVEN department policy on changing tracks.

Departmental Requirements
In addition to fulfilling the University requirements for the Doctor of Philosophy (Ph.D.) degree, a student enrolled in the Civil Engineering graduate program in the area of Artificial Intelligence and Data Science area must satisfy the following department requirements.

A minimum of 32 credit hours of graduate-level coursework taken through Texas A&M University [a minimum of 24 credit hours if the student already has taken at least another 24 credit hours of graduate course work for the Master of Science (M.S.) or Master of Engineering (MEng) degree].
Remaining coursework requirement can be met by 32 hours of CVEN 691.

Artificial Intelligence and Data Science Requirements
The student must also satisfy the following area requirements and/or recommendations described below:

Qualifying Exam
Degree Plan
Written Preliminary Exam
Research Proposal
Oral Preliminary Exam
Completion of Dissertation
Final Defense

Dissertation Topic
Students pursuing the AI/DS track would work on dissertation topics with a great extent of interdisciplinary elements spanning across civil engineering and computer science/AI. Such interdisciplinary research would require a student to develop depth of knowledge and skills across both domains.

Committee
The committee of Ph.D. students in the AI/DS track can be composed of faculty from different departments with backgrounds and skills related to the subject matter of the dissertation research.

Qualification Exam
The qualification exam will involve both a written and oral exam. The written exam will involve two components: 1. Domain problem, and 2. AI/DS methods. For the domain problem, students are provided with a number of state-of-the-art journal publications related to their dissertation topic and are asked to perform a critical review and assess the merits and limitations of the studies and their methods. For the AI/DS methods part, students are provided with questions related to the fundamentals of AI/DS methods. The purpose of this part of the written exam is to evaluate the basic knowledge and programming skills of the students. Each part of the written exam will be held on separate days. The oral part of the qualification exam will focus on the dissertation topic of the students and the research they have conducted up to this point.

Students in the AI/DS track are strongly encouraged to form their dissertation committee prior to the qualification exam. If the dissertation committee is formed prior to the qualification exam, the exam questions will be developed by the committee in coordination with the AI/DS Track Coordinator. If the student's dissertation committee is not formed at the time of the qualification examination, the Track Coordinator and the student advisor will handle the development of the qualification examination.

Coursework
Students in the AI/DS track can take any courses related to the topic of their dissertation research (both civil eng. domain problem and the AI/DS methods). The selection of courses to be included in the degree plan should be based on the Ph.D. advisor and committee recommendation. The following are examples of courses that students in the AI/DS track may choose to take:

AI and Data Science associated courses by course number, title and department.
Course	Title	Department
650	STAT FND DATA SCIENCE	STAT
647	SPATIAL STATISTICS	STAT
616	STAT ASPECTS OF MACH LEARN I	STAT
765	MACH LEARN WITH NETWORKS	ECEN
654	STAT COMPUTING WITH R & PYTHON	STAT
651	STAT IN RESEARCH I	STAT
633	MACHINE LEARNING	CSCE
639	DATA MINING & ANALYSIS	STAT
689	SPTP: NETWORK SCI OF CITIES	URSC
651	STAT IN RESEARCH I	STAT
689	SPTP: NETWORK SCIENCE OF CITIES	URSC
689	SPTP: PROGRAMING IN URBAN ANALYTICS	URSC
689	Machine Intelligence and Applications in CE	CVEN