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Computer Science

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Note: This is the 2018–2019 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .

Computer Science

Location

Location

  • School of Computer Science
  • McConnell Engineering, Room 318
  • 3480 University Street
  • Montreal QC H3A 0E9
  • Canada
  • Telephone: 514-398-7071, ext. 00074
  • Fax: 514-398-3883
  • Email: grad.cs [at] mcgill.ca
  • Website:

About Computer Science

About Computer Science

The School of Computer Science is one of the leading teaching and research centres for computer science in Canada. We offer several M.Sc. programs and a Ph.D. program; all include coursework and research. In the basic M.Sc. programs, students must choose between the thesis option, and the non-thesis option, which requires a project. The Ph.D. program includes an option in bioinformatics, and the thesis M.Sc. program includes options in bioinformatics and in Computational Science and Engineering. Students are normally funded by their adviser's research grants; in the case of scholarship students, this typically takes the form of a 'top-up' to the scholarship. Research in the School covers a broad range of areas, including:

  • Theory: algorithms, combinatorial optimization, computational geometry, cryptography, graph theory, logic and computation, programming languages, quantum computing, theory of computation, and scientific computing;
  • Systems: compilers, computer games, distributed systems, embedded and real-time systems, modelling and simulations, networks, and software engineering;
  • Applications: bioinformatics, machine learning, robotics, computer animation, graphics, and vision.

All students must consult the , where up-to-date information about the graduate programs is posted. Any questions concerning programs should be addressed to the .

Master of Science (M.Sc.) Computer Science (Thesis) (45 credits)

This program is designed for students with a strong interest in research in computer science who hold at least the equivalent of an undergraduate minor in CS. This program combines a strong course component with a research thesis. It is the usual (but not mandatory) entry point for students who wish to do a Ph.D., but is also the program of choice for students who want to find challenging and exciting jobs after their master's.

Master of Science (M.Sc.) Computer Science (Thesis): Bioinformatics (45 credits)

Bioinformatics research lies at the intersection of biological/medical sciences and mathematics/computer science/engineering. The intention of the Bioinformatics option is to train students to become researchers in this interdisciplinary field. This includes the development of strategies for experimental design, the construction of tools to analyze datasets, the application of modelling techniques, the creation of tools for manipulating bioinformatics data, the integration of biological databases, and the use of algorithms and statistics.

Master of Science (M.Sc.) Computer Science (Thesis): Computational Science & Engineering (45 credits)

This program option is to train graduates in state-of-the-art applications of numerical and modelling methods and computer technology to scientific and engineering problems. CSE is a rapidly growing multidisciplinary area with connections to the sciences, engineering, mathematics, and computer science.

Master of Science (M.Sc.) Computer Science (Non-Thesis) (45 credits)

This program is designed for students who want to obtain broad knowledge of advanced topics in computer science but without the requirement of a thesis. It offers an excellent preparation for the job market, but is not recommended for students interested in eventually pursuing a Ph.D.

Doctor of Philosophy (Ph.D.) Computer Science

The Ph.D. program trains students to become strong, independent researchers in the field of their choice. Our graduates take challenging positions in industry or take academic positions at universities and research labs. In order to apply to the Ph.D. program, applicants should normally hold a master's degree in Computer Science or a closely related area, from a well-recognized university, but exceptional students can be admitted to the Ph.D. program directly without a master's degree.

Doctor of Philosophy (Ph.D.) Computer Science: Bioinformatics

Bioinformatics research lies at the intersection of biological/medical sciences and mathematics/computer science/engineering. The intention of the Bioinformatics option is to train students to become researchers in this interdisciplinary field. This includes the development of strategies for experimental design, the construction of tools to analyze datasets, the application of modelling techniques, the creation of tools for manipulating bioinformatics data, the integration of biological databases and the use of algorithms and statistics.

Programs, Courses and University Regulations—2018-2019 (last updated Aug. 16, 2018) (disclaimer)

Computer Science Admission Requirements and Application Procedures

Computer Science Admission Requirements and Application Procedures

Admission Requirements

Admission Requirements

Master’s (M.Sc.)

The minimum requirement for admission is a bachelor's degree (cumulative grade point average (CGPA) of 3.2 out of 4.0 or better, or equivalent) with the coursework in Computer Science as listed on our .

The website supplements the information in this publication, and should be consulted by all graduate students.

Ph.D.

In order to apply to the Ph.D. program, applicants should hold an M.Sc. degree in Computer Science or a closely related area, from a well-recognized university. Students who hold a B.Sc. degree in Computer Science but have an exceptionally strong academic record may be admitted directly to the Ph.D. program, but they must initially apply to the M.Sc. program. Students who are in the M.Sc. program have the option to be fast-tracked into the Ph.D. program at the end of their first academic year, contingent on excellent performance as judged by the Ph.D. committee.

Application Procedures

Application Procedures

³ÉÈËVRÊÓƵ’s online application form for graduate program candidates is available at www.mcgill.ca/gradapplicants/apply.

See University Regulations & Resources > Graduate > Graduate ³ÉÈËVRÊÓƵ and Application Procedures > Application Procedures for detailed application procedures.

Additional Requirements

Additional Requirements

The items and clarifications below are additional requirements set by this department:

  • Curriculum Vitae – required for both M.Sc. and Ph.D. programs
  • Statement of Purpose – required for both M.Sc. and Ph.D. programs
  • (GRE General Test) – required for degrees from outside Canada. Optional for Ph.D. program.

Application Dates and Deadlines

Application Dates and Deadlines

Application opening dates are set by Enrolment Services in consultation with Graduate and Postdoctoral Studies (GPS), while application deadlines are set by the School of Computer Science and may be revised at any time. Applicants must verify all deadlines and documentation requirements well in advance on the appropriate ³ÉÈËVRÊÓƵ departmental website; please consult the list at www.mcgill.ca/gps/contact/graduate-program.

Ìý Application Opening Dates Application Deadlines
Ìý All Applicants Non-Canadian citizens (incl. Special, Visiting & Exchange) Canadian citizens/Perm. residents of Canada (incl. Special, Visiting & Exchange) Current ³ÉÈËVRÊÓƵ Students (any citizenship)
Fall Term: Sept. 15 March 1 March 1 March 1
Winter Term: (*Ph.D. only) Feb. 15* Sept. 1* Sept. 1* Sept. 1*
Summer Term: N/A N/A N/A N/A

Admission to graduate studies is competitive; accordingly, late and/or incomplete applications are considered only as time and space permit.

For further details on our admission requirements, please visit our website at .

Scholarship Deadlines: January 1 for applicants who wish to be considered for scholarship awards; otherwise, March 1 for admission to the Fall term.
Programs, Courses and University Regulations—2018-2019 (last updated Aug. 16, 2018) (disclaimer)

Computer Science Faculty

Computer Science Faculty

Director
B. Kemme
Emeritus Professors
D. Avis; B.Sc.(Wat.), Ph.D.(Stan.)
R. De Mori; Ph.D.(Politecnico Torino)
T.H. Merrett; B.Sc.(Qu.), D.Phil.(Oxf.)
M.M. Newborn; B.E.E.(Rensselaer Poly.), Ph.D.(Ohio St.), F.A.C.M.
C. Paige; B.Sc., B.Eng.(Syd.), Ph.D.(Lond.)
G.F.G. Ratzer; B.Sc.(Glas.), M.Sc.(McG.)
D. Thérien; B.Sc.(Montr.), M.Sc., Ph.D.(Wat.) (James ³ÉÈËVRÊÓƵ Professor)
G.T. Toussaint; B.Sc.(Tulsa), Ph.D.(Br. Col.)
Post-Retirement
C. Tropper; B.Sc.(McG.), Ph.D.(Brooklyn Poly.)
Professors
L. Devroye; M.S.(Louvain), Ph.D.(Texas) (James ³ÉÈËVRÊÓƵ Professor)
G. Dudek; B.Sc.(Qu.), M.Sc., Ph.D.(Tor.) (James ³ÉÈËVRÊÓƵ Professor)
L. Hendren; B.Sc., M.Sc.(Qu.), Ph.D.(Cornell), F.R.S.C. (Canada Research Chair)
X. Liu; B.Sc., M.Sc.(Tsinghua), Ph.D.(Ill.) (William Dawson Scholar)
P. Panangaden; M.Sc.(IIT, Kanpur), M.S.(Chic.), Ph.D.(Wisc.)
B. Reed; B.Sc., Ph.D.(McG.) (Canada Research Chair)
M. Robillard; B.Eng.(École Poly., Montr.), M.Sc., Ph.D.(Br. Col.)
K. Siddiqi; B.Sc.(Lafayette), M.Sc., Ph.D.(Brown) (William Dawson Chair)
Associate Professors
M. Blanchette; B.Sc., M.Sc.(Montr.), Ph.D.(Wash.)
X.W. Chang; B.Sc., M.Sc.(Nanjing), Ph.D.(McG.)
C. Crépeau; B.Sc., M.Sc.(Montr.), Ph.D.(MIT)
N. Friedman; B.A.(W. Ont.), Ph.D.(Tor.)
H. Hatami; B.Sc.(Sharif), M.Sc., Ph.D.(Tor.)
B. Kemme; B.Sc., M.Sc.(Erlangen-Nuremberg, Germany), Ph.D.(ETH, Zurich)
J. Kienzle; Eng.Dip., Ph.D.(Swiss Fed. IT)
P. Kry; B.Sc.(Wat.), M.Sc., Ph.D.(Br. Col.)
M. Langer; B.Sc.(McG.), M.Sc.(Tor.), Ph.D.(McG.)
M. Maheswaran; B.Sc.(U. Peradeniya), M.Sc., Ph.D.(Purdue)
B. Pientka; B.Sc., M.Sc.(Tech. U. of Darmstadt, Germany), Ph.D.(Carn. Mell)
J. Pineau; B.Sc.(Wat.), M.Sc., Ph.D.(Carn. Mell) (William Dawson Scholar)
D. Precup; B.Sc.(Tech. U. of Cluj-Napoca), M.Sc., Ph.D.(Mass.)
D. Ruths; B.Sc., M.Sc., Ph.D.(Rice)
C. Verbrugge; B.A.(Qu.), Ph.D.(McG.)
A. Vetta; B.Sc., M.Sc.(LSE), Ph.D.(MIT)
J. Waldispuhl; B.Sc.(Nice Sophia Antipolis), M.Sc.(Paris VII), Ph.D.(École Poly., France)
Assistant Professors
Y. Cai; B.S.(Peking), M.S., Ph.D.(MIT) (William Dawson Scholar)
J. Cheung; B.Sc.(Br. Col.), M.Sc., Ph.D.(Tor.)
D.Meger; B.Sc.(Br. Col.), M.Sc.(McG.), Ph.D.(Br. Col.)
Faculty Lecturer
J. Vybihal; B.Sc., M.Sc.(McG.)
Associate Members
D. Schlimm (Philosophy)
T.R. Shultz (Psychology)
Adjunct Professors
A. Baretto, P.J. Mosterman, T. Perkins, I. Rekleitis, G.O. Sabidussi
Programs, Courses and University Regulations—2018-2019 (last updated Aug. 16, 2018) (disclaimer)

Master of Science (M.Sc.) Computer Science (Thesis) (45 credits)

Master of Science (M.Sc.) Computer Science (Thesis): Bioinformatics (45 credits)

Master of Science (M.Sc.) Computer Science (Thesis): Computational Science & Engineering (45 credits)

Thesis Courses (24 credits)

24 credits selected from:

COMP 691 (3) Thesis Research 1
COMP 696 (3) Thesis Research 2
COMP 697 (4) Thesis Research 3
COMP 698 (10) Thesis Research 4
COMP 699 (12) Thesis Research 5

Required Courses

One credit selected as follows:

COMP 669D1 (.5) Computational Science Engineering Seminar
COMP 669D2 (.5) Computational Science Engineering Seminar

and

COMP 601 (2) Thesis Literature Review

Complementary Courses

(minimum 20 credits)

At least 6 courses whereby at least two courses must be from List A, at least two courses from List B, and the remaining credits to be chosen from graduate (500-, 600-, or 700-level) courses in the School of Computer Science. Two complementary courses must be taken outside the School of Computer Science.

Note: Students with an appropriate background can substitute 3 credits by COMP 696 and 4 credits by COMP 697, but still need to take 6-8 credits from List A and 6-8 credits from List B.

List A: Scientific Computing Courses:

CIVE 602 (4) Finite Element Analysis
COMP 522 (4) Modelling and Simulation
COMP 540 (3) Matrix Computations
COMP 566 (3) Discrete Optimization 1
MATH 578 (4) Numerical Analysis 1
MATH 579 (4) Numerical Differential Equations

List B: Application and Specialized Methods Courses:

ATOC 512 (3) Atmospheric and Oceanic Dynamics
ATOC 513 (3) Waves and Stability
ATOC 515 (3) Turbulence in Atmosphere and Oceans
CIVE 572 (3) Computational Hydraulics
CIVE 603 (4) Structural Dynamics
COMP 557 (3) Fundamentals of Computer Graphics
COMP 558 (3) Fundamentals of Computer Vision
COMP 567 (3) Discrete Optimization 2
COMP 621 (4) Program Analysis and Transformations
COMP 642 (4) Numerical Estimation Methods
COMP 767 (4) Advanced Topics: Applications 2
ECSE 507 (3) Optimization and Optimal Control
ECSE 532 (3) Computer Graphics
ECSE 547 (3) Finite Elements in Electrical Engineering
ECSE 549 (3) Expert Systems in Electrical Design
MATH 555 (4) Fluid Dynamics
MATH 560 (4) Optimization
MATH 761 (4) Advanced Topics in Applied Mathematics 1
MECH 533 (3) Subsonic Aerodynamics
MECH 537 (3) High-Speed Aerodynamics
MECH 538 (3) Unsteady Aerodynamics
MECH 539 (3) Computational Aerodynamics
MECH 541 (3) Kinematic Synthesis
MECH 572 (3) Introduction to Robotics
MECH 573 (3) Mechanics of Robotic Systems
MECH 577 (3) Optimum Design
MECH 610 (4) Fundamentals of Fluid Dynamics
MECH 620 (4) Advanced Computational Aerodynamics
MECH 632 (4) Advanced Mechanics of Materials
MECH 642 (4) Advanced Dynamics
MECH 650 (4) Fundamentals of Heat Transfer
MECH 654 (4) Compt. Fluid Flow and Heat Transfer
Programs, Courses and University Regulations—2018-2019 (last updated Aug. 16, 2018) (disclaimer)

Master of Science (M.Sc.) Computer Science (Non-Thesis) (45 credits)

Doctor of Philosophy (Ph.D.) Computer Science

Required coursework: Students must take eight graduate courses, of which at least five are computer science courses. These courses should be chosen by the student in consultation with the supervisor (or co-supervisor) and the Progress Committee.

For more information, see Doctor of Philosophy (Ph.D.) Computer Science.

Doctor of Philosophy (Ph.D.) Computer Science: Bioinformatics

Faculty of Science—2018-2019 (last updated Aug. 16, 2018) (disclaimer)
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