Master of Science in Computer science

Prerequisite: 1501371 or equivalents or written consent of instructor.

The course concentrates on developing and analyzing algorithms for problems, which arise in various applications such as shortest path problems, depth first search and applications, general matching, planarity testing, graph colorability, etc. Depending on the year and instructor, a treatment of topics such as, randomized algorithms, average case analysis of algorithms, the class of #P and algorithms for enumeration problems may be covered.

Prerequisite: 1501366 or equivalent.

Conventional methodologies such as Structured, JSD, SADT, etc.; OO paradigm; OO design methodologies (OMT, Booch's, Yourdon's methodologies): a comparative study; conversion from imperative to OO designs. Evaluation of OO designs and software metrics. Use of OO methodologies in various application domains such as multimedia, hypermedia, etc. Automation of the methodologies; OO design evaluation. Case Study.

Prerequisite: Grad Standing.

This course explores the research process in general and the resources for research in computer science. Traditional research approaches and use of emerging technology will be discussed. Attendance at Department seminars and classes is required.

Prerequisite: Grad Standing.

This course helps the student explore specific areas of interest or enables him/her to develop in-depth research in a field of interest. The topic should be related to the area of interest in which the student is planning to prepare his/her thesis. The course helps the student to develop his/her critical thinking and analysis. The registration in this course and its topic should be approved in advance by the student's potential thesis supervisor and the program coordinator.

Prerequisite: Completion of 12 credits.

The student has to undertake and complete a research topic in Computer Science under the supervision of a faculty member. The thesis work should provide the student with in-depth perspective of a particular research problem in his chosen field of specialization of Computer Science. It is anticipated that the student be able to carry out this theoretical research and required practical work fairly independently under the direction of the supervisor. The student is required to submit a final thesis documenting the research, experiments, findings and defend the work in front of a committee.

Prerequisite: Completion of 12 credits.

Prerequisite: Grad Standing.

Learning problems; concept learning; decision tree learning; artificial neural networks; genetic algorithms; inductive and analytical learning; case-based reasoning; explanation-based learning; and knowledge-based artificial neural networks.

Prerequisite: Grad Standing.

Image processing basics; image segmentation and region analysis; thresholding; connected component labelling; pattern recognition; morphology; image and video; motion detection and compensation; stereo vision and depth perception; knowledge-based vision; biometrics-based authentication and identification; and special-purpose computers for vision applications.

Prerequisite: Grad Standing.

Principles and properties of lighting models such as Phong shading, ray tracing and radiosity; a selection of visualization and modeling techniques; 2D and 3D animation techniques; and color and human perception.

Prerequisite: Grad Standing.

Various topics can be covered subject to the interest of the students and the availability of faculty. Such topics include: natural language processing; machine translation; speech processing; foundations and applications of logic programming; intelligent computer-aided design; etc.

Prerequisite: 1501371 or equivalents.

Algorithmic fundamentals of robotics: representing rigid bodies, polyhedral models, representing rotations, configuration space; elementary notions from algorithms and geometry: computational complexity, O notation, graph search techniques, convex hull, intersection detection, algorithms for distance calculations; gross motion planning: global motion planning, local collision avoidance, planning with non-holonomic constraints, and path planning in dynamic environments.

Prerequisite: 1501371 or equivalents.

The design and analysis of algorithms for geometric problems including convexity, intersection, triangulation, search, proximity and optimization. Lower bound arguments, NP-completeness results, probabilistic algorithms, approximation algorithms, dynamization techniques, and other issues applicable to geometric problems. Applications of geometric algorithms are emphasized.

Prerequisite: Grad Standing.

Topics of current research interest in advanced graphics and human interfaces, chosen from such areas as intelligent user interfaces, user modeling, user interface design, visualization, computer animation, advanced multimedia, and computer-based training using visual display, touch, gesture, and marking; speech, language, and audition; subject to the interests and availability of faculty.

Prerequisite: Grad Standing.

Resource sharing; computer traffic characterizations; layered network structure; network design and optimization; network protocols; routing, flow control and extended error control techniques; introduction to formal techniques for protocol specification, and verification and testing.

Prerequisite: Grad Standing.

Principles and practice of parallel computing; design, implementation, and evaluation of parallel programs for shared-memory architectures, local-memory architectures, and vector processors.

Prerequisite: 1501352 or equivalent.

Centralized and distributed operating systems; distributed system structures; synchronization in distributed systems; processes and processors in distributed systems; distributed shared memory; protection and security. Distributed file systems.

Prerequisite: 1501263 or equivalent.

Fundamental concepts in database management systems; Web as a medium for sharing and interoperating databases across the Internet; mathematical models and measurements of the Web; URL sampling and search engines; data integration and interchange; XML solutions; querying XML data; storing XML data; data mining, and selected topics.

Prerequisite: Grad Standing.

Study of formal methods in software engineering: formal specification; algebraic specification; model-based specification; inductive specification; automated program transformation; automated test generation; towards automated program maintenance.

Prerequisite: Grad Standing.

OO data modeling; OO DBs; version management; schema evolution; query processing and optimization; transaction management; authorization and security in OO databases; client/server environment and distributed databases; and deductive databases.

Prerequisite: Grad Standing.

In this course, students will study various malicious software attacking computer systems and networks. Most of these attacks are caused by the vulnerabilities in the design and implementation of computer systems. Students will learn different techniques to evaluate the security of computer systems and detect common vulnerabilities. They will also appreciate security principles and standards to write secure code. Students are required to conduct research on the course topics and write a review paper. A project is also required.