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Computing and Information Science

MSc Program


Wlodek Dobosiewicz (313 Reynolds, Ext. 2250)
(E-mail: chair@cis.uoguelph.ca)

Graduate co-ordinator
Yang Xiang, (1389 Thornborough, Ext. 2824)
(E-mail: yxiang@cis.uoguelph.ca)

Graduate secretary
Colleen O'Brien (312 Reynolds, Ext. 6402)

Graduate Faculty
Dilip K. Banerji
BTech Indian Inst. of Tech., MSc Ottawa, PhD Waterloo - Professor

David A. Calvert
B.A. Hnrs. Guelph, M.Sc. Guelph, PhD Waterloo - Assistant Professor

David K.Y. Chiu
BA Waterloo, BSc Guelph, MSc Queen's, PhD Waterloo - Professor

Wlodek Dobosiewicz
BSc, MA, MSc, PhD Warsaw - Chair & Professor

Gary Gréwal
BSc Brock, M.Sc. Guelph, Ph.D. Guelph - Assistant Professor

Stefan C. Kremer
B.Sc. Hnrs. Guelph, Ph.D. Alberta - Assistant Professor

Xining Li
BSc, MSc Nanjing, PhD Calgary - Professor

James G. Linders
BASc, MASc Toronto, PhD Imperial College, London - Professor

Jay C. Majithia
BSc London, MEng, PhD McMaster - Professor Emeritus

Charlie F. Obimbo
MSc Kiev, PhD New Brunswick - Assistant Professor

Deborah A. Stacey
BSc Guelph, PhD Waterloo - Associate Professor

David A. Swayne
BSc Waterloo, MA York, PhD Waterloo - Professor

Fangju Wang
BE Changsha, MSc Peking, PhD Waterloo - Associate Professor

Thomas C. Wilson
BA Iowa, MSc Chicago, PhD Waterloo - Professor

Mark Wineberg
BSc Toronto, MSc, Phd Carleton - Assistant Professor

Michael A. Wirth
BSc New England (Aust.), MSc Manitoba, PhD RMIT Melbourne - Assistant Professor

Yang Xiang
BSs, MSc BUAA (Beijing), PhD UBC - Associate Professor

Associated Graduate Faculty
Brian Ross
BSc Manitoba, MSc British Columbia, PhD Edinburgh - Adjunct Professor

     The Department of Computing and Information Science offers a program of study leading to the MSc degree in applied computer science.

MSc Program

     The MSc program has a distinctive applied orientation, emphasizing research that can potentially contribute to industry and government. Interaction with other disciplines is encouraged. The program is based on three areas of technical specialization: (1) parallel and distributed computing, (2) interactive software environments, and (3) artificial intelligence. A software engineering initiative is underway and students will be considered in this area. Research in the department is conducted by groups centred in these areas of activity. Research in distributed systems includes distributed databases, VLSI design automation, computer architecture and networks, and parallel processing. Research in interactive software environments includes human-computer interaction, user-interface software and hypertext. Research in artificial intelligence includes uncertainty management, knowledge acquisition, expert systems, image processing, neural networks and pattern recognition. In addition, applied research is carried out in areas such as information management, including geographical-information systems, statistical databases, and office information systems.

Admission Requirements
     To be considered for admission, applicants must meet the minimum admission requirements of both the university and the department, including at least a 75% ('B') average during the previous four semesters of university study. Applicants must possess a four-year honours degree in computer science. However, a student with a minor in computer science and an honours degree in another applicable discipline may be granted provisional admission. Owing to the applied nature of the program, we encourage students with such backgrounds to apply. To assist in identifying a suitable thesis adviser, applicants are requested to submit descriptions of their research interests.
     Most available spaces will be filled in May for entry the following September. A limited amount of spaces are available in January with admission given in the previous October.

Degree Requirements
     Degree requirements include a master's thesis, participation in a research seminar and at least four graduate-level courses: two in the student's research area and others outside of that area. There is no qualifying exam or second-language requirement. Heavy emphasis is placed on the thesis, which usually requires at least two semesters. Students should plan on spending at least four full-time semesters in the program assuming adequate preparation for graduate work. Normally, students are expected to fulfill all the requirements in five semesters.
     Graduate courses are organized around the areas of specialization mentioned earlier. The courses chosen must include at least two of these areas. In exceptional cases, one graduate-course requirement may be met by an approved 0.5-credit graduate course from another department or by two approved 400-level 0.5-credit courses which have not already been taken for credit. The specific course requirements for each student will be determined in consultation with the thesis adviser and advisory committee, subject to the above constraints.


Course/(Credit Value) Term Course Description
Distributed Systems
Distributed Systems (0.5)
   The evolution of high-performance distributed computer systems. Models for distributed processing. Taxonomy and performance evaluation of multiprocessor systems. Interconnection networks. Memory and I/O system for multiprocessor architectures. Performance of distributed systems. Architectural issues of distributed database systems.
Parallel Processing (0.5)
   Introduction to parallel processing. Discussion of possible alternative architectures such as bus architecture and n-cube architecture machines. Comparison of SISD, SIMD, MISD and MIMD machines. The complexity of sorting and other algorithms in a parallel-processing context. Topics may include systolic processing and/or array processing.
Design Automation in Digital Systems (0.5)
   Techniques and software tools that provide a computer-aided-design (CAD) facility to designers of digital systems. Most of the material will be on high-level synthesis and optimizations, sufficiently abstracted from circuit/logic-level details.
Topics in Distributed Systems (0.5)
   Selected topics in distributed systems that are not covered by existing courses. The topics will be chosen from: local-area networks, distributed databases, performance evaluation and reliability, introduction to VLSI.
Interactive Software Environments
Interactive Software Tools (0.5)
   Recent advances in understanding the development of interactive software. Topics include conceptual paradigms for interactive software, tools for developing interactive software, knowledge-based tools and human factors of software development.
Models for Design of Human-Computer Interaction (0.5)
   Formal and informal models applicable to the design of human-computer interaction. Topics include history of human-computer interaction models, models of users, models of interactions, models of interactive systems, and models of the design and development process.
Research in Design Methods for Human-Computer Interaction (0.5)
   Current developments in design methods for human-computer interaction. Topics include the history of design methods in human-computer interaction, the acquisition and formalization of design knowledge and advanced techniques in user interfaces (e.g., knowledge-based interfaces).
Topics in Interactive-Software Environments (0.5)
   Topics of current interest to the department and students and not covered by existing courses. The topics will be chosen from: CAI applications, human-factor research in software development, applied cognitive science for human-computer interaction, office software environments.
Artificial Intelligence
Knowledge Representation and Expert Systems (0.5)
   The major features of expert systems today: a discussion of logic and rule-based systems; forward and backward chaining; frames, scripts, semantic nets and the object-oriented approach; the evaluation of expert systems and knowledge acquisition. A sizeable project is required and applications in other areas are encouraged.
Uncertainty Reasoning in Intelligence Systems (0.5)
   Different paradigms for handling uncertainty in reasoning. Topics include the incorporation of uncertainty into logical models, e.g., fuzzy logic, probabilistic logic and non-nontonic reasoning; and introduction to Dempster- Shafer theory. The role of belief networks, complexity issues. Applications will be presented and a project required.
Pattern Recognition and Machine Learning (0.5)
   An interdisciplinary approach to knowledge discovery, machine learning and pattern analysis. Possible topics include: information measures, inductive learning, statistical and structural pattern recognition, neural networks, applications in computational molecular biology and image analysis.
Image Processing Algorithms and Applications (0.5)
   Topics in image processing algorithms, and their analysis and implementation. The emphasis is on representation and data structures, analysis of algorithms and complexities, parallel architectures and algorithms for image processing, as well as implementation issues including image-processing language design and software-development environments.
Artificial Neural Networks (0.5)
   An introductory survey course concentrating on analysis of various artificial neural network models in terms of their underlying principles, topologies, behaviours and learning algorithms. Some applications will also be discussed.
Topics in Artificial Intelligence (0.5)
   Topics in areas of artificial intelligence that are of current interest to the department and students that are not covered by existing courses. Possible topics include search, planning; natural language understanding; special topics in knowledge representation, robotics, knowledge-based modelling, intelligent databases and decision support systems.
Other Miscellaneous Courses
Complexity of Parallel Computation (0.5)
   Computing models, sequential model, complexity models, evolution of parallelism, parallel complexity, P-completeness, survey of P and NC, open problems.
Software Systems Development and Integration (0.25)
   Techniques and tools used in the development of large software systems. Methods for organizing and constructing modular systems, manipulating files, an introduction to interface design, and use of databases. Software tools for managing projects, database connectivity, configuration management, and system application programmer interfaces.
The Analysis and Design of Computer Algorithms (0.25)
   The design and analysis of efficient computer algorithms: standard methodologies, asymptotic behaviour, optimality, lower bounds, implementation considerations, graph algorithms, matrix computations (e.g. Strassen's method), NP-completeness.
Topics in Information Management (0.5)
   This course will cover topics in a variety of areas of information management that are of current interest to the department and students. Possible topics include geographical-information systems, object-oriented databases, statistical databases, spatial databases, office-information systems.
Topics in Computer Science (0.5)
   This course will cover selected topics in computer science that are of current interest to the department and students. The topics include advanced algorithms and computational complexity, theory of parsing and compilation, database theory.
Computer Science Seminar (0.0)
   A regular weekly seminar presenting research problems currently under investigation. Each student is expected to regularly attend for three semesters and to present one of the talks.


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