Intelligent Systems and Data Science

Doctor of Philosophy in Intelligent Systems and Data Science

Dean

Peter Berg

Faculty of Mathematics and Science

Associate Dean

Melanie Pilkington

Faculty of Mathematics and Science

Core Faculty

Professors

S. Ejaz Ahmed (Mathematics and Statistics), Stephen Anco (Mathematics and Statistics), Hichem Ben-El-Mechaiekh (Mathematics and Statistics), Chantal Buteau (Mathematics and Statistics), Henryk Fuks (Mathematics and Statistics), Sheridan Houghten (Computer Science), Omar Kihel (Mathematics and Statistics), Yuanlin Li (Mathematics and Statistics), Alexander Odesskii (Mathematics and Statistics), Beatrice Ombuki-Berman (Computer Science), Ke Qiu (Computer Science), Brian Ross (Computer Science), Jan Vrbik (Mathematics and Statistics), Michael Winter (Computer Science), Thomas Wolf (Mathematics and Statistics), Xiaojian Xu (Mathematics and Statistics)

Associate Professor

Robson De Grande (Computer Science), William Marshall (Mathematics and Statistics)

Assistant Professors

Glaucio H.S. de Carvalho (Computer Science and Engineering), Renata Dividino (Computer Science), Ali Emami (Computer Science), Naser Ezzati-Jivan (Computer Science), Tianyu Guan (Mathematics and Statistics), Yifeng Li (Computer Science), Pouria Ramazi (Mathematics and Statistics)

Participating Graduate Faculty

Professor

Ping Liang (Biological Sciences)

Graduate Program Director

Ke Qiu

kqiu@brocku.ca

Elena Genkin

FMS Graduate Administrative Coordinator

905 688 5550, extension 3115

Mackenzie Chown D473

egenkin@brocku.ca

Administrative Assistant (Computer Science)

Brittani Allan

905-688-5550, extension3513

Mackenzie Chown J314

ballan@brocku.ca

Administrative Assistant (Math and Statictics)

Alan Liu

905-688-5550, extension 3300

Mackenzie Chown J415

hliu@brocku.ca

Program Description

The Department of Computer Science and Department of Mathematics and Statistics offers a program leading to the PhD in Intelligent Systems and Data Science (PhD) degree. The program focuses on the complementary roles of intelligent systems and data science, and their role in solving complex real-world applications. Graduate research topics may be conducted in a number of broad areas, including artificial intelligence, smart systems, and data science. Please see Department web pages for a listing of faculty and their research interests.

Admission Requirements

There are three ways in which students may be admitted: (i) Students holding an MSc in Computer Science, Mathematics, Statistics, or a closely related discipline with a minimum 80% overall average from an accredited institution. (ii) Students currently in the MSc program may apply to transfer into the PhD program after one year of study if they have completed the required number of courses in their program with an average of at least 80% and have shown significant research progress as determined by their supervisory committee and graduate program committee. (iii) In exceptional cases, students may be admitted into the PhD program with a four-year Honours Bachelor's degree, or the equivalent, in Computer Science, Mathematics, Statistics, or a closely related discipline, with an overall average of at least an 85%. These students must demonstrate high research potential adjudicated by the graduate program committee.

The Graduate Admissions Committee will review all applications and recommend admission for a limited number of candidates. Part-time study is available in exceptional cases only for students admitted through option (i) above.

Degree Requirements

All candidates must complete the following requirements:

Course Requirements: All students must complete ISDS 7P75 and ISDS 7N01 (normally taken together in the same term) as well as ISDS 7F90. Students admitted through option (i) or (ii) must complete an additional four half-credit courses; students admitted through option (iii) must complete an additional six half-credit courses. Course selection is done in consultation with the supervisor. One half-credit graduate course can be taken from a different department related to applications of intelligent systems and data science, or applied computing, with the approval of the supervisor and course instructor. All other courses must be COSC or MATH/STAT half-credit courses at the 5(alpha)00 level or above.

Qualifying examination: After all course requirements, excepting ISDS 7F90, have been completed, but within the first 24 months of the program, all students must successfully complete a qualifying examination. Prior to the exam, the student must submit a written proposal of research in the form of an NSERC PGS D grant application or, in the case of students planning a career in industry, a MITACS grant application or other industry appropriate funding source grant application. The student will be guided by the supervisor and the supervisory committee while preparing this application. The examination committee consists of the supervisory committee. The examination will start with a presentation by the student about his/her research, followed by questions from the examination committee about this research. The outcome of the examination is pass/fail. The examination can be repeated once within four months.

Thesis and Thesis Defence: Before the thesis is submitted for defence, parts of the thesis must be published in, or at least submitted to, an international journal or conference. The supervisory committee will decide whether a thesis is ready for defence. The examination committee is chaired by the Dean of Graduate Studies or designate, and consists of the supervisory committee, an internal examiner (from outside the graduate program but within Brock University), and an external examiner. The defence is open and will start with a presentation by the student about his/her research, followed by questions from the examination committee.

Facilities

A campus-wide fiber optic network links all of the university's academic computing facilities. The departments' computers form an integral part of this resource. All faculty and graduate students are provided with an account on the departmental and/or university servers. Most computers on campus can be accessed from microcomputers in any of the laboratories.

Brock is also a full member of the SHARCnet consortium with access to all its high-performance clusters of powerful workstations.

In addition to three servers, the departments maintain several PC based labs and UNIX workstations for teaching and research.

Course Descriptions

Note that not all courses are offered in every session. Refer to the applicable timetable for details.

Students must ensure that prerequisites are met. Students may be deregistered, at the request of the instructor, from any course for which prerequisites and/or restrictions have not been met.

ISDS 7F90

PhD Research and Thesis

Original theoretical and/or experimental research and thesis. An external examiner will participate in the final thesis defence to evaluate the student's performance in this course.

ISDS 7N01

Scientific Writing

The organizational and stylistic skills of writing and referencing a scientific document. Examples from the various literature forms such as primary journals, reviews, reports, and theses, as well as presentations and seminars. Database use and reference citation, and use of figures and graphs to illustrate data.

Note: Normally taken in conjunction with ISDS 7P75.

ISDS 7P75

PhD Seminar

Preparation of a thesis proposal, including a written document and public presentation. Successful completion will indicate that a student is adequately prepared to commence thesis research.

Note: Normally taken in conjunction with ISDS 7N01.