Computer Science

Computer Science: Introduction

Faculty Affiliation

Arts and Science

Degree Programs

Applied Computing

MScAC

  • Concentrations:
    • Applied Mathematics;
    • Artificial Intelligence;
    • Data Science;
    • Quantum Computing

Computer Science

MSc and PhD

Collaborative Specializations

The following collaborative specializations are available to students in participating degree programs as listed below:

Overview

Graduate faculty in the Department of Computer Science are interested in a wide range of subjects related to computing, including programming languages and methodology, software engineering, operating systems, compilers, distributed computation, networks, numerical analysis and scientific computing, data structures, algorithm design and analysis, computational complexity, cryptography, combinatorics, graph theory, artificial intelligence, neural networks, knowledge representation, computational linguistics and natural language processing, computer vision, robotics, database systems, graphics, animation, interactive computing, and human-computer interaction.

For further details, consult the graduate student handbook prepared by the department and available online.

Contact and Address

MSc and PhD Programs

Web: cs.toronto.edu
Email: gradapplications@cs.toronto.edu
Telephone: (416) 978-8762

Department of Computer Science Graduate Office
University of Toronto
Bahen Centre for Information Technology
40 St. George Street
Toronto, Ontario M5S 2E4
Canada

MScAC Program

Web: mscac.utoronto.ca
Email: mscac@cs.toronto.edu
Telephone: (416) 978-5180

University of Toronto
700 University Avenue, 9th Floor
Toronto, ON M5G 1Z5
Canada

Computer Science: Graduate Faculty

Full Members

Abdelrahman, Tarek - BSc, MSc, PhD
Amza, Cristiana - BS, MS, PhD
Anderson, Ashton Chandler Justin - BEng, MSc, PhD
Aspuru-Guzik, Alan - PhD
Ba, Jimmy - PhD, PhD, PhD
Bacchus, Fahiem - BS, SM, PhD
Bader, Gary - BSc, PhD
Balakrishnan, Ravin - BS, SM, PhD
Beck, Chris - BSc, MSc, PhD
Bonner, Anthony - BSc, MSc, PhD
Borodin, Allan - BS, SM, PhD, FAAAS
Brudno, Michael - AB, SM, PhD
Burgner-Kahrs, Jessica - PhD
Chechik, Marsha - BS, SM, PhD
Christara, Christina - BS, SM, PhD
de Lara, Eyal - BS, MS, PhD (Chair and Graduate Chair)
Demke Brown, Angela - BS, SM, PhD
Dickinson, Sven Josef - BASc, MS, PhD
Easterbrook, Steve - BSc, PhD
Ellen, Faith - BM, MMath, PhD
Enright Jerger, Natalie - BSc, MSc, PhD
Fairgrieve, Thomas - BMath, MSc, PhD
Farzan, Azadeh - BS, PhD
Fidler, Sanja - PhD
Fleet, David James - BS, MS, PhD
Fox, Mark - BSc, PhD
Ganjali, Yashar - BSc, MSc, PhD
Garg, Animesh - BE, MS, MS, PhD
Gilitschenski, Igor - PhD
Goel, Ashvin - BTech, MS, PhD
Goldenberg, Anna - PhD
Grinspun, Eitan - PhD
Grossman, Tovi - PhD
Gruninger, Michael - BSc, MS, PhD
Gupta, Arvind - BSc, PhD
Hadzilacos, Vassos - BSE, PhD
Hirst, Graeme - BA, BSc, MSc, PhD (Associate Chair, Graduate Studies)
Khalvati, Farzad - MASc, PhD
Koudas, Nick - BS, MS, PhD
Kutulakos, Kyros - BS, MSc, PhD
Lyons, Kelly - BSc, MSc, PhD
Maddison, Christopher - PhD
Marbach, Peter Josef - DipIng, MS, PhD
Mariakakis, Alexander - PhD
McIlraith, Sheila - BSc, MSc, PhD
Mihailidis, Alex - BASc, MASc, PhD
Molloy, Michael - BMath, MMath, PhD
Morris, Quaid - BS, PhD
Moses, Alan - BA, PhD
Moshovos, Andreas - BSc, MS, PhD
Munteanu, Cosmin - MSc, MASc, PhD
Nikolov, Aleksandar - PhD
Pekhimenko, Gennady - BS, MS, PhD
Penn, Gerald - BS, MSc, PhD
Pitassi, Toniann - BS, SM, PhD
Roth, Frederick - PhD
Roy, Daniel - BS, MEng, PhD
Rudzicz, Frank - PhD
Sachdeva, Sushant - BTech, MA, PhD
Schroeder, Bianca - MSc, PhD
Shah, Nisarg - PhD
Shkurti, Florian - BSc, MSc
Singh, Karan - BS, MS, PhD
Soden, Robert - PhD
Stevenson, Suzanne Ava - MS, PhD
Strug, Lisa - BS, BA, SM, PhD
Stumm, Michael - MS, PhD
Taati, Babak - PhD
Tang, Tony - PhD
Toueg, Sam - BS, MA, MSEE, PhD
Truong, Khai Nhut - BSc, PhD
Urtasun, Raquel - PhD
Vijaykumar, Nandita - BE, ME
Wang, Bo - BS, MS, PhD
Wiebe, Nathan - PhD
Wigdor, Daniel - PhD
Xu, Yang - PhD
Yu, Eric - BSc, MMath, PhD
Zemel, Richard - BA, SM, PhD
Zhang, Zhaolei - BS, PhD

Members Emeriti

Cook, Stephen - BS, SM, PhD
Corneil, Derek - BSc, MA, PhD
Fiume, Eugene - BM, MSc, PhD
Hinton, Geoffrey E. - BA, PhD
Jackson, Kenneth - BSc, MSc, PhD
Jepson, Allan - BSc, PhD
Miller, Renee - BS, BM, MS, PhD
Neal, Radford - BSc, MSc, PhD
Rackoff, Charles - SB, SM, PhD

Associate Members

Armstrong, Blair - BASc, MA, PhD
Campbell, Jennifer - BSc, MMath
Campbell, Kieran - PhD
Craig, Michelle - BSc, MSc
Engels, Steve - BASc, MMath
Gries, Paul - BA, MSc
Heap, Daniel - BS, MSc
Hoffman, Michael - PhD
Horton, Diane - BS, MSc
Kelly, Jonathan - BSc, MS, MSc, PhD
Kim, Philip - BS, PhD
Kreinin, Alexander - MSc, PhD
Lee, Annie - PhD
McIntosh, Chris - PhD
Papernot, Nicolas - BS, MSc, PhD
Papyan, Vardan - BSc, MSc, PhD
Pitt, Francois - BSc, MSc, PhD
Reid, Karen - BS, MB, MS
Rost, Hannes - PhD
Tsotsos, John - BASc, MSc, PhD, CRC
Yuan, Ding - PhD

Computer Science: Applied Computing MScAC

Master of Science in Applied Computing

Program Description

The Master of Science in Applied Computing (MScAC) program is offered as

  • a general Computer Science program (no concentration) or as

  • a concentration in:

    • Applied Mathematics, offered jointly by the Department of Computer Science and the Department of Mathematics;

    • Artificial Intelligence, offered jointly by the Department of Computer Science, the Department of Statistical Sciences, and the Faculty of Engineering and Applied Science;

    • Data Science, offered jointly by the Department of Computer Science and the Department of Statistical Sciences;

    • Quantum Computing, offered jointly by the Department of Computer Science and the Department of Physics.

There is no thesis requirement.

 

MScAC General Program (No Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor's degree from a recognized university in computer science or a related discipline.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) and International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of support from faculty and/or employers.

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

Program Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:

    • 1.0 FCE in required courses: technical communications (CSC2701H) and technical entrepreneurship (CSC2702H).

  • An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F)

Time Limit

3 years full-time

 

MScAC Program (Applied Mathematics Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor’s degree from a recognized university in a related area such as applied mathematics, computational mathematics, computer science, mathematics, physics, statistics, or any discipline where there is a significant mathematical component. The completed bachelor’s degree must include coursework in advanced and multivariate calculus (preferably analysis), linear algebra, and probability. In addition, there should be some depth in at least two of the following six areas:

    • analysis (for example, measure and integration, harmonic analysis, functional analysis);

    • discrete math (for example, algebra, combinatorics, graph theory);

    • foundations (for example, complexity theory, set theory, logic, model theory);

    • geometry and topology;

    • numerical analysis; and

    • ordinary and partial differential equations.

    There should also be a demonstrated capacity at programming and algorithms.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in computer science and mathematics, and in an industrial internship in applied mathematics. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science, mathematics, and a domain area. Applicants may be asked to do a technical interview as part of the application process.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) and International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Mathematics or Applied Mathematics.

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

  • Applicants must indicate a preference for the concentration in Applied Mathematics in their application. Admission is competitive, and students who are admitted to the MScAc program are not automatically admitted to this concentration upon request.

Program Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE chosen from the MAT1000-level courses or higher.

    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings.

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists (0.5 FCE) and

      • CSC2702H Technical Entrepreneurship (0.5 FCE).

    • Course selections should be made in consultation with the Program Director.

  • An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F)

Time Limit

3 years full-time

 

MScAC Program (Artificial Intelligence Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor’s degree from a recognized university in a related area such as physics, computer science, mathematics, statistics, engineering, or any discipline where there is a significant quantitative component. The completed bachelor’s degree must include significant exposure to computer science or statistics or engineering including coursework in advanced and multivariate calculus (preferably analysis), linear algebra, probability and statistics, programming languages, and general computational methods.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) and International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Artificial Intelligence (AI).

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

  • Applicants must indicate a preference for the concentration in AI in their application. Admission to the AI concentration is competitive. Students who are admitted to the MScAc program are not automatically admitted to the AI concentration upon request.

Program Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.5 FCEs of coursework in the area of AI:

      • 1.0 FCE selected from the core list of AI courses (see list below) from at least two different research areas

      • 0.5 FCE selected from additional AI courses outside the core list

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists (0.5 FCE)

      • CSC2702H Technical Entrepreneurship (0.5 FCE)

    • Remaining 0.5 FCE of coursework will be chosen from outside of AI:

      • Course selections should be made in consultation with and approved by the Program Director. Appropriate substitutions may be possible with approval.

      • A maximum of 1.0 FCE may be chosen from outside the Computer Science (CSC course designator) graduate course listing.

  • An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F)

Time Limit

3 years full-time

Artificial Intelligence Core Courses

Course Code Course Title
AER1513H State Estimation for Aerospace Vehicles
AER1517H Control for Robotics
CSC2501H Computational Linguistics
CSC2502H Knowledge Representation and Reasoning
CSC2503H Foundations of Computer Vision
CSC2511H Natural Language Computing
CSC2515H* Introduction to Machine Learning (exclusion: ECE1513H)
CSC2516H** Neural Networks and Deep Learning (exclusion: MIE1517H)
CSC2533H Foundations of Knowledge Representation
CSC2630H Introduction to Mobile Robotics
ECE1512H Digital Image Processing and Applications
ECE1513H* Introduction to Machine Learning (exclusion: CSC2515H)
MIE1517H** Introduction to Deep Learning (exclusion: CSC2516H)

*different courses with the same title, offered by different Faculties.
**different courses with similar titles, offered by different Faculties.

 

MScAC Program (Data Science Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor’s degree from a recognized university in a related area such as statistics, computer science, mathematics, or any discipline where there is a significant quantitative component.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants must satisfy the admissions committee of their ability to be successful in graduate courses in computer science, statistics, and an industrial internship in data science. Applicants may be asked to do a technical interview as part of the application process.

  • The program will consider admitting candidates without an undergraduate degree in computer science, statistics, or a related field, but who show a demonstrated aptitude to be an excellent data scientist. Applicants should be able to demonstrate a potential to conduct and communicate applied research at the intersection of computer science, statistics, and a domain area. Background academic preparation to be successful in graduate-level computer science and statistics courses typically, though not always, includes intermediate or advanced undergraduate courses in the following topics:

    • Algorithms and Complexity, Database Systems, or Operating Systems.

    • Statistical Theory/Mathematical Statistics, Probability Theory, or Regression Analysis.

  • Students who are otherwise qualified but lack the appropriate background may be granted conditional admission, pending successful completion of additional background material as judged by the admissions committee.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) and International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of support from faculty and/or employers.

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

  • Applicants must indicate a preference for the concentration in Data Science in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.

Program Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) including:

    • 1.0 FCE chosen from the STA2000-level courses or higher. This may include a maximum of 0.5 FCE chosen from the STA4500-level of six-week modular courses (0.25 FCE each).

    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings.

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists (0.5 FCE) and

      • CSC2702H Technical Entrepreneurship (0.5 FCE).

    • Course selections should be made in consultation with the Program Director.

  • An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F)

Time Limit

3 years full-time

 

MScAC Program (Quantum Computing Concentration)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor’s degree from a recognized university in a related area such as physics, computer science, mathematics, or any discipline where there is a significant quantitative component. The completed bachelor’s degree must include significant exposure to physics, computer science, and mathematics, including coursework in advanced quantum mechanics, multivariate calculus, linear algebra, probability and statistics, programming languages, and computational methods.

  • A standing equivalent to at least B+ in the final year of undergraduate studies.

  • Applicants whose primary language is not English and who have graduated from a university where the primary language of instruction is not English must submit results of the Test of English as a Foreign Language (TOEFL) and International English Language Testing System (IELTS) with the following minimum scores:

    • Internet-based TOEFL: 93/120 and 22/30 on the writing and speaking sections.

    • IELTS: an overall score of 7.0, with at least 6.5 for each component.

  • If students complete a portion of their degree in English, or part of their degree at another university where English is the language of instruction, applicants must still provide proof of English-language proficiency.

  • Three letters of reference from faculty and/or employers, with preference for at least one such letter from a faculty member in Physics.

  • Applicants will be asked to respond to program-specific questions addressing their interest in the concentration and objectives for the program.

  • Applicants must indicate a preference for the concentration in Quantum Computing in their application. Admission is competitive, and students who are admitted to the MScAC program are not automatically admitted to this concentration upon request.

Program Requirements

  • Coursework. Students must successfully complete a total of 3.0 full-course equivalents (FCEs) as follows:

    • 1.0 FCE chosen from the Physics (PHY course designator) graduate course listings. Of eligible courses, the following are examples that are particularly relevant to the Quantum Computing concentration:

      • PHY1500H Statistical Mechanics (0.5 FCE)

      • PHY1520H Quantum Mechanics (0.5 FCE)

      • PHY1610H Scientific Computing for Physicists (0.5 FCE)

      • PHY2203H Quantum Optics I (0.5 FCE)

      • PHY2204H Quantum Optics II (0.5 FCE)

      • PHY2212H Entanglement Physics (0.5 FCE)

    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings. Of eligible courses, the following are examples that are particularly relevant to the Quantum Computing concentration:

      • CSC2305H Numerical Methods for Optimization Problems (0.5 FCE)

      • CSC2421H Topics in Algorithms (0.5 FCE)

      • CSC2451H Quantum Computing, Foundations to Frontier (0.5 FCE)

    • 1.0 FCE in required courses:

      • CSC2701H Communication for Computer Scientists (0.5 FCE)

      • CSC2702H Technical Entrepreneurship (0.5 FCE)

    • Course selections should be made in consultation with the Program Director. Appropriate substitutions may be possible with approval.

  • An eight-month industrial internship, CSC2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F)

Time Limit

3 years full-time

Computer Science: Computer Science MSc

Master of Science

Program Description

The MSc degree program is designed for students seeking to be trained as a researcher capable of creating original, internationally recognized research in computer science.

The MSc program can be taken on a full-time or part-time basis.

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • An appropriate bachelor's degree with a standing equivalent to at least a University of Toronto B+. Preference is given to applicants who have studied computer science or a closely related discipline.

  • Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.

Program Requirements

  • Coursework. Completion of 2.0 graduate full-course equivalents (FCEs) in computer science. The courses must satisfy breadth in three of the four different Methodologies of Computer Science to ensure that MSc graduates have a breadth of skills for research and problem solving throughout their careers.

  • A major research paper (CSC4000Y; 1.0 FCE) demonstrating the student's ability to do independent work in organizing existing concepts and in suggesting and developing new approaches to solving problems in a research area. The standard for this paper is that it could reasonably be submitted for peer-reviewed publication.

Program Length

4 sessions full-time (typical registration sequence: F/W/S/F);
8 sessions part-time

Time Limit

3 years full-time;
6 years part-time

Computer Science: Computer Science PhD

Doctor of Philosophy

Program Description

The PhD degree program is designed for students seeking to be trained as a researcher capable of creating original, internationally recognized research in computer science. Research conducted under the supervision of a faculty member will constitute a significant and original contribution to computer science.

Applicants may enter the PhD program via one of two routes: 1) following completion of an appropriate master’s degree or 2) direct entry following completion of a bachelor’s degree.

 

PhD Program

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • Successful completion of an appropriate master's degree with a standing equivalent to at least a University of Toronto B+. Preference is given to applicants who have studied computer science or a closely related discipline.

  • Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); or 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.

Program Requirements

  • Coursework. Students must complete 2.0 full-course equivalents (FCEs) and a thesis.

  • The courses must satisfy breadth in four different research areas of computer science to ensure a broad and well-balanced knowledge of computer science.

  • Students must meet the department's timeline for satisfactory progress as outlined in the PhD handbook.

  • A meeting of the PhD supervisory committee must be held by the 16th month of the PhD program. This is typically the initial meeting with the supervisory committee and is referred to as the qualifying oral examination. After the qualifying oral, the student's PhD supervisory committee must meet at least once annually. The student must have their thesis topic approved at a PhD supervisory committee meeting within the time frame for achieving candidacy. The departmental thesis examination must be passed before the SGS Final Oral Examination can be scheduled.

Program Length

4 years

Time Limit

6 years

 

PhD Program (Direct-Entry)

Minimum Admission Requirements

  • Applicants are admitted under the General Regulations of the School of Graduate Studies. Applicants must also satisfy the Department of Computer Science's additional admission requirements stated below.

  • Applicants may be admitted to this program directly from a bachelor's degree with a standing equivalent to at least a University of Toronto A–. Preference is given to applicants who have studied computer science or a closely related discipline.

  • Applicants whose primary language is not English and who graduated from a university where the language of instruction is not English must achieve a Test of English as a Foreign Language (TOEFL) score of at least 580 on the paper-based test and 4 on the Test of Written English (TWE); or 93/120 on the Internet-based test and 22/30 on the writing and speaking sections.

Program Requirements

  • Coursework. Students must complete 4.0 full-course equivalents (FCEs) and a thesis.

  • The courses must satisfy breadth in four different research areas and three different methodologies of computer science to ensure a broad and well-balanced knowledge of computer science.

  • Students must meet the department's timeline for satisfactory progress as outlined in the PhD handbook.

  • A meeting of the PhD supervisory committee must be held by the 16th month of the PhD program. This is typically the initial meeting with the supervisory committee and is referred to as the qualifying oral examination. After the qualifying oral, the student's PhD supervisory committee must meet at least once annually. The student must have their thesis topic approved at a PhD supervisory committee meeting within the time frame for achieving candidacy. The departmental thesis examination must be passed before the SGS Final Oral Examination can be scheduled.

Program Length

5 years

Time Limit

7 years

Computer Science: Computer Science MScAC, MSc, PhD Courses

Not all courses are offered every year. Please consult the department for course offerings.

Course Code Course Title
CSC2104H
Formal Methods of Program Design
CSC2107H
Compilers and Interpreters
CSC2108H Automated Verification
CSC2125H
Topics in Software Engineering
CSC2130H Empirical Research Methods in Software Engineering
(Exclusion: ECE1785H.)
CSC2206H
Computer Systems Modelling
CSC2208H
Advanced Operating Systems
CSC2209H
Computer Networks
CSC2221H
Introduction to Distributed Computing
CSC2222H Applications of Parallel and Distributed Computing
CSC2224H Parallel Computer Architecture and Programming
CSC2226H
Topics in Verification
CSC2227H
Topics in the Design and Implementation of Operating Systems
CSC2228H
Topics in Mobile, Pervasive, and Cloud Computing
CSC2231H
Topics in Computer Systems
CSC2233H
Topics in Storage Systems
CSC2240H Graphs, Matrices, and Optimization
CSC2302H Numerical Solutions of Initial Value Problems for Ordinary Differential Equations
CSC2305H
Numerical Methods for Optimization Problems
CSC2306H
High Performance Scientific Computing
CSC2310H
Computational Methods for Partial Differential Equations
CSC2321H
Matrix Calculations
CSC2326H
Topics in Numerical Analysis
CSC2332H Introduction to Quantum Algorithms
(Prerequisite: good knowledge of linear algebra and elementary real and complex analysis.)
CSC2401H Introduction to Computational Complexity
CSC2404H
Computability and Logic
CSC2405H Automata Theory
CSC2410H Introduction to Graph Theory
CSC2412H Algorithms for Private Data Analysis
(Prerequisite: CSC373 or equivalent, or permission of the instructor.)
CSC2415H
Advanced Topics in the Theory of Distributed Computing
CSC2416H
Machine Learning Theory
CSC2417H Algorithms for Genome Sequence Analysis
CSC2419H Topics in Cryptography
CSC2420H Algorithm Design, Analysis, and Theory
CSC2421H Topics in Algorithms
CSC2426H
Fundamentals of Cryptography
CSC2429H
Topics in the Theory of Computation
CSC2431H Topics in Computational Biology and Medicine
CSC2451H Quantum Computing, Foundations to Frontier
(Exclusion: MAT1751H Quantum Computing, Foundations to Frontier.)
CSC2501H
Computational Linguistics
CSC2502H
Knowledge Representation and Reasoning
CSC2503H
Foundations of Computer Vision
CSC2504H Computer Graphics
CSC2506H
Probabilistic Learning and Reasoning
CSC2508H Advanced Data Systems
CSC2510H Topics in Information Systems
CSC2511H
Natural Language Computing
CSC2512H
Constraint Satisfaction Problems
CSC2513H Critical Thinking for Human Computer Interaction
(Prerequisite: CSC318 or equivalent, or permission of the instructor.)
CSC2514H Human-Computer Interaction
CSC2515H
Introduction to Machine Learning
(Exclusion: ECE1513H.)
CSC2516H Neural Networks and Deep Learning
(Exclusion: MIE1517H.)
CSC2517H Discrete Mathematical Models of Sentence Structure
CSC2518H
Spoken Language Processing
CSC2520H Geometry Processing
CSC2521H Topics in Computer Graphics
CSC2523H
Object Modelling and Recognition
CSC2524H Topics in Interactive Computing
CSC2525H Research Topics in Database Management
CSC2526H HCI: Topics in Ubiquitous Computing
CSC2527H The Business of Software
CSC2528H
Advanced Computational Linguistics
CSC2529H Computational Imaging
CSC2530H Computer Vision for Advanced Digital Photography
CSC2532H
Statistical Learning Theory
(Prerequisite: CSC2515H.)
CSC2533H
Foundations of Knowledge Representation
CSC2536H Topics in Computer Science and Education
CSC2537H Information Visualization
CSC2539H
Topics in Computer Vision
CSC2540H Computational Cognitive Models of Language
CSC2541H
Topics in Machine Learning
CSC2542H
Topics in Knowledge Representation and Reasoning
CSC2545H Advanced Topics in Machine Learning
(Prerequisite: CSC2515H or equivalent is recommended.)
CSC2546H Computational Neuroscience
CSC2547H Current Algorithms and Techniques in Machine Learning
CSC2548H Machine Learning in Computer Vision
CSC2549H Physics-Based Animation
CSC2552H Topics in Computational Social Science
CSC2556H Algorithms for Collective Decision Making
CSC2558H Topics in Multidisciplinary HCI
CSC2559H Trustworthy Machine Learning
CSC2600H Topics in Computer Science
CSC2604H Topics in Human-Centred and Interdisciplinary Computing
CSC2606H Introduction to Continuum Robotics
(Prerequisite: Introduction to Robotics; e.g, CSC376 offered at UTM or AER525. Exclusion: CSC476 offered at UTM.)
CSC2611H Computational Models of Semantic Change
CSC2612H Computing and Global Development
(Prerequisite: CSC 318 or equivalent, or permission of the instructor.)
CSC2615H Ethical Aspects of Artificial Intelligence
CSC2621H Topics in Robotics
(Prerequisite: CSC411H or CSC2515H.)
CSC2626H Imitation Learning for Robotics
(Prerequisite: CSC411/2515 Machine Learning and Data Mining or equivalent.)
CSC2630H Introduction to Mobile Robotics
(Required prerequisites: CSC209H, MAT223H, MAT232H, and STA256 or equivalent. Recommended prerequisites: CSC311H, CSC376H, CSC384H, and MAT224H or equivalent. Exclusions: AER1513H, CSC477H.)
CSC2699H Special Reading Course in Computer Science
CSC2701H
Communication for Computer Scientists
CSC2702H
Technical Entrepreneurship
CSC2703H
MScAC Internship
CSC2720H
Systems Thinking for Global Problems
CSC4000Y MSc Research Project in Computer Science