Graduate Programme in
Computer Science

Admission Brochure 2002-2003

FIELDS OF STUDY

Our M.Sc. programme covers a wide variety of subdisciplines. Our Ph.D. programme concentrates on real-time and concurrent systems; artificial intelligence, computer vision, graphics and robotics; and parallel algorithms and architectures.

DEGREE REQUIREMENTS

Masters Degree Requirements

Candidates for the M.Sc. degree must complete five graduate three-credit courses and successfully defend a Master's thesis if they choose the Thesis option. If the Project option is taken, candidates are to complete seven graduate courses and do a project. Candidates must conduct a piece of approved research under the direction of a Thesis or Project supervisor. There is also a breadth requirement on the selected graduate courses. Students are expected to complete all of their Masters degree requirements in no more than five terms (twenty months). For more details refer to the programme's supplemental calendar http://www.cs.yorku.ca/grad/calendar.html.

Doctoral Degree Requirements

Candidates for the Ph.D degree must complete at least three three-credit graduate courses to satisfy both breadth and depth requirements. Candidates must successfully complete a qualifying examination consisting of a written report on the Candidate's field of interest and defend it. Candidates must present a dissertation proposal outlining the anticipated results of their dissertation. Candidates are required to enroll in either an industrial internship or a teaching practicum. Finally, Candidates must conduct a significant body of original research under the supervision of a supervisory committee and successfully defend the resulting dissertation. Students are expected to complete their requirements in no more than four years. For more details refer to the programme's supplemental calendar.

ADMISSION REQUIREMENTS

Applications must include official copies of all academic transcripts, 3 letters of reference and a one page statement of purpose and previous experience. The statement of purpose should indicate the applicant's area(s) of interest in Computer Science.

The following are the minimum English Language test scores (if required): TOEFL 233/577 or YELT 4. The GRE general test + Computer Science subject test is required for applicants who did their work oustide of Canada and the US (subject to approval).

Potential applicants may find the following document of frequently asked admissions questions useful: http://www.cs.yorku.ca/grad/faq.html

Master of Science Programme

Graduates with an honours degree in Computer Science or equivalent, with at least a B+ average in the last two years of study, may be admitted as Candidates for the Masters programme in Computer Science. In addition, those admitted must have completed the equivalent of a senior-level course in the area of theoretical computer science.

For part-time M.Sc. applicants the application must include a letter from the employer indicating that they support the applicant and will give them appropriate time off to take the various courses and work on the thesis/project.

Doctor of Philosophy Programme

Applicants must have an M.Sc. degree equivalent to the M.Sc. Computer Science degree at York University. The York M.Sc. Computer Science degree is based upon course work and a defended thesis. A minimum average grade of B+ on all course work is required.

Applications must include a breadth statement and an extended abstract/copy of the M.Sc. thesis. The breadth statement indicates the graduate courses taken and is broken down in three groups (see the courses section below).

FINANCIAL SUPPORT

All full-time M.Sc. students are normally given financial support for their first five terms (20 months) in the programme. The level of support is $18,000/year. Students who are awarded an external scholarship can receive up to $28,000/year.

All full-time Ph.D students are normally given financial support for their first twelve terms (48 months) in the programme. The level of support is $22,000/year. Students who are awarded an external scholarship can receive up to $32,000/year.

For more details refer to the programme's supplemental calendar.

COURSES

Not all courses listed are offered each year. For detailed descriptions check the programme's supplemental calendar. 5xxx courses are typically integrated with 4-th year undergraduate courses.

Group 1: Theory of Computing and Scientific Computing

COSC5101.03 Advanced Data Structures
COSC5111.03 Automata, Computability and Complexity
COSC6112.03 Parallel Algorithms
COSC6113.03 Computability
COSC6114.03 Computational Geometry
COSC6115.03 Computational Complexity
COSC6116.03: Advanced Computational Complexity
COSC6190A.03: Online Computing
COSC6190B.03: Coarse Grained Parallel Computing
COSC6211.03 Numerical Linear Algebra
COSC6212.03 Sparse Matrices

Group 2: Artificial Intelligence and Interactive Systems

COSC5311.03 Logic Programming
COSC5323.03 Computer Vision
COSC5324.03 An Introduction to Robotics
COSC5325.03: Signals & Systems
COSC5326.03: Topics in Artificial Intelligence
COSC5331.03 Introduction to Computer Graphics
COSC5341.03: Real-Time Systems Theory
COSC5342.03: Real-Time Systems Practice
COSC6311.03 Programming Logic for Complex Systems
COSC6323.03: Advanced Topics in Computer Vision
COSC6324.03: From Control to Actuators
COSC6325.03: Mobile Robot Motion Planning
COSC6331.03: Advanced Image Synthesis
COSC6341.03: Methods for Large-Scale Software Development
COSC6342.03: Object Oriented Software Construction
COSC6390A.03: Knowledge Representation
COSC6390B.03: Scheduling in Hard Real-Time Systems
COSC6390C.03: Advanced Human-Computer Interaction

Group 3: Systems: Software and Hardware

COSC5411.03 Database Management Systems
COSC5421.03 Operating System Design
COSC5422.03 Performance Evaluation of Computer Systems
COSC5423.03 Programming Language Design
COSC5424.03 Language Processors
COSC6422.03: Parallel and Distributed Computing
COSC6423.03: Parallel Computing on Networks of Workstations
COSC6431.03: Software Re-Engineering
COSC6490A.03: Concurrent Object-Oriented Languages
COSC6490B.03: Issues in Information Integration
COSC6490C.03: Decision Support Systems
COSC6490D.03: Software Reuse
COSC6490E.03: Reasoning in Databases
COSC5501.03 Computer Architecture
COSC6501.03 Introduction to Parallel Computer Architectures
COSC6502.03 Computational Aspects of VLSI
COSC6590A.03 High-Performance Computer Networks

FACULTY RESEARCH

MOKHTAR ABOELAZE: Ph.D. (Purdue). Associate Professor of Computer Science. Computer architecture. Parallel processing (multiprocessors and vector processors). Systolic arrays. Performance evaluation of computer systems and networks.

ROBERT S. ALLISON: Ph.D. (York). Assistant Professor of Computer Science. Biological and computational vision especially stereopsis. Eye movement measurement and analysis. Virtual environments.

JOHN AMANATIDES: Ph.D. (Toronto). Associate Professor of Computer Science. Computer graphics. Realistic image synthesis. Ray tracing, shading, illuminant models, antialiasing.

ESHRAT ARJOMANDI: Ph.D. (Toronto). Professor of Computer Science. Most recently her research has concentrated on efficient memory allocation and garbage collection techniques in programming languages. She is also interested in object-oriented programming techniques and how these techniques may be utilized in concurrent programming.

FRANCK VAN BREUGEL: Ph.D. (Free University, Amsterdam). Assistant Professor of Computer Science. Concurrent programming languages: design, implementation, verification and programming.

SUPRAKASH DATTA: Ph.D. (Massachusetts). Assistant Professor of Computer Science. Parallel and distributed computation, performance evaluation, network modelling.

PATRICK W. DYMOND: Ph.D. (Toronto). Professor of Computer Science. Complexity theory, parallel algorithms and architectures.

JEFF EDMONDS: Ph.D. (Toronto). Associate Professor of Computer Science. Complexity, lower bounds, algorithms, combinatorics, probability theory, scheduling.

JAMES ELDER: Ph.D. (McGill). Assistant Professor of Psychology, Adjunct Professor of Computer Science. Computer vision, visual psychophysics, image coding, image editing, virtual reality.

PARKE GODFREY: Ph.D. (Maryland). Assistant Professor of Computer Science. Database systems.

JAREK GRYZ: Ph.D. (Maryland). Assistant Professor of Computer Science. Database systems.

MICHAEL R.M. JENKIN: Ph.D. (Toronto). Professor of Computer Science. Computer vision with a particular emphasis on stereopsis. Mobile robotics. Virtual Reality.

RICHARD HORNSEY: Ph.D. (Oxford). Associate Professor of Computer Science. Integrated electronic sensors, biologically inspired image sensors, low vision enhancement systems, sensors for space applications.

MARIANA KANT: Ph.D. (Université de Montreal). Associate Professor of Computer Science (Glendon). BioInformatics. Design and Analysis of Algorithms (sequential, parallel, distributed) Distributed and Heterogeneous Databases. Internet applications.

YVES LESPERANCE: Ph.D. (Toronto). Associate Professor of Computer Science. Artificial Intelligence, knowledge representation and reasoning, intelligent agents.

JOSEPH W.H. LIU: Ph.D. (Waterloo). Professor of Computer Science. Sparse matrix technology. Large scale scientific computation. Vector/parallel computing. Scientific software development. Graph algorithms. Scientific visualization.

SCOTT MACKENZIE: Ph.D. (Toronto). Associate Professor of Computer Science. Input devices and interactive techniques for advanced and mobile computing; human performance measurement, prediction, and modeling.

EVANGELOS E. MILIOS: Ph.D. (MIT). Associate Professor of Computer Science. Shape representation and matching. Sensor-based robot exploration and navigation. Knowledge-based signal processing and interpretation.

ANDRANIK MIRZAIAN: Ph.D. (Princeton). Associate Professor of Computer Science. Computational Geometry. Combinatorial optimization and graph algorithms. Computational robotics and program animation.

JONATHAN S. OSTROFF: Ph.D. (Toronto). Associate Professor of Computer Science. Design of real-time software for reactive systems such as safety critical medical systems, nuclear plants, communication systems and robots. The use of formal methods for modeling, specification and automated verification of complex systems. CASE tools for formal methods. Software engineering.

RICH PAIGE: Ph.D. (Toronto). Assistant Professor of Computer Science. Software engineering, method integration, tool integration, formal methods and theorem provers, high-level circuit design, compilers, object-oriented programming and design.

EUGENE ROVENTA: Ph.D. (Timisoara). Associate Professor of Computer Science (Glendon). Artificial Intelligence (Intelligent Computation, Logic Problem Solving, Knowledge Representation and Processing of Imprecise and / or Uncertain Knowledge) and Non Classical Measures.

ERIC RUPPERT: Ph.D. (Toronto). Assistant Professor of Computer Science. Models of Distributed Computing, Distributed Algorithms, Computability and Computational Complexity.

ARTHUR RYMAN: Ph.D. (Oxford). Adjunct Professor of Computer Science. Architect for VisualAge for Java, IBM Application Development Technology Centre. Software engineering, software design technology.

MINAS E. SPETSAKIS: Ph.D. (Maryland). Associate Professor of Computer Science. Computer Vision. Robotics.

ZBIGNIEW STACHNIAK: Ph.D. (Wroclaw, Poland). Associate Professor of Computer Science. Computational logic and Knowledge Representation: methodology of automated reasoning and theorem proving systems, computer science and applied logics. Logic Programming.

STERGIOS STERGIOPOULOS: Ph.D. (York). Adjunct Professor of Computer Science. Adaptive and Synthetic Aperture Signal processing with emphasis on sonar, ultrasound and medical tomography imaging X-ray CT and MRI system applications.

WOLFGANG STUERZLINGER : Ph.D. (Vienna University of Technology, Austria). Assistant Professor of Computer Science. Computer graphics and human-computer interaction. Real-time rendering, image-based modeling and rendering, user interfaces for interaction with virtual environments.

GEORGE TOURLAKIS: Ph.D. (Toronto). Professor of Computer Science. Logic (classical, calculational, modal), Computability theory (computation with partial function oracles, arithmetical forcing), Complexity theory.

JOHN TSOTSOS: Ph.D. (Toronto). Professor or Computer Science. Director, Centre for Vision Research. Computational Vision with a current major focus being the modelling of visual attention.

WALTER J. WHITELEY: Ph.D. (MIT). Professor of Mathematics. Discrete geometry and its applications, rigidity (static and kinematics) of frameworks, multivariate splines, polyhedral combinatorics, matroid theory, logic and invariant theory, diagrammatic reasoning, geometric constraints in parametric CAD.

HUGH R. WILSON: Ph.D. (University of Chicago). ORDCF Professor of Biological & Computational Vision. Psychophysical & computational studies of human form vision & motion perception Neural modeling & nonlinear dynamics in vision Functional brain imaging (fMRI) of the human visual system

JIA XU: Ph.D. (Louvain). Associate Professor of Computer Science. Real-time systems, including real-time operating systems, real-time database systems, real-time communication systems, real-time embedded systems.

FACILITIES

The Computer Science facility, which can be accessed remotely by dial-up and through the Internet, consists of large Sun servers, Sun and SGI workstations and color X- terminals. The laboratories include Vision, Graphics and Robotics Lab with SGI and Sun workstations equipped with multi-media hardware including video and audio facilities, a robot along with access to an RWI mobile robot a number of Nomad mobile robots in various types and sizes, a wireless iRobot Magellan Pro autonomous mobile robot and two CRS robot arms. The Laboratory for Computer Systems Research (LCSR) consists of Sun and Dell workstations. The Multi-media Lab has resources for creating and editing audio and broadcast-quality video and is equipped with PCs and Macs. The Real-time Lab allows students to conduct experiments involving real-time systems programming and safety analysis of reactive software and is equipped with a digital train-set, a PC and a Sun workstation. In addition, there is a 100- seat X terminal workstation and undergraduate lab and interconnection to several large timesharing computers running Unix on the network. An SGI 16-processor Origin 2000 with 8 GB of memory is available. As well, a 6-sided Virtual Reality Cave driven by a 16-processor 3-pipe SGI Reality Monster is being completed. X terminals are available in each of the graduate student and faculty offices. The technical staff that runs these labs consists of 6 people.

HOW TO CONTACT US

Our main web page is: http://www.cs.yorku.ca/grad/
E-mail enquiries: gradinfo@cs.yorku.ca

Our physical address is:

        Graduate Programme in Computer Science,
        York University
        4700 Keele Street
        Toronto, Ontario  M3J 1P3
        Canada

Telephone (416) 736-2100 extension 66183
Fax (416) 736-5872

Revised: July 18, 2001