Fall 2006 CS Course Listings

This file contains the Fall 2006 course listings for the Department of Computer Science and Engineering.

Archive of past courses

Course Code: COMP524
Course Title: Computer Vision

Instructor: Chi-Keung Tang
Room: 3561
Telephone: X-8775
Email:
WWW page: https://course.cse.ust.hk/comp524/ (use the CSD username and password to log on)
Area in which course can be counted: Vision & Graphics

Course description:

  • Introduction to techniques for automatically describing visual data and tools for image analysis;
  • perception of spatial organization;
  • models of general purpose vision systems;
  • computational and psychological models of perception.

Notes:

  • Students should have the background of COMP 271 or equivalent.
  • A good working knowledge of C and C++ programming; Linear algebra; Some mathematical sophistication

Course outline/content (by major topics):

  1. Introduction
  2. Image formation
  3. Image filtering
  4. Edge detection
  5. Segmentation
  6. Segmentation II
  7. Projective geometry
  8. Image warping
  9. Motion estimation
  10. Stereo
  11. Tensor voting
  12. Multiview stereo (minor update)
  13. Light
  14. Recognition

Text book:

  • Computer Vision: A Modern Approach, D. Forsyth and J. Ponce

Reference books/materials:

  • Three-Dimensional Computer Vision, O. Faugeras, MIT Press, 1993
  • Multiple View Geometry in computer vision , R. Hartley and A. Zisserman, Cambridge University Press, 2000
  • Robot Vision, B.K.P. Horn, MIT Press, 1986
  • A Guided Tour of Computer Vision, V. S. Nalwa, Addison Wesley, 1993
  • Machine Perception, R. Nevatia, Prentice-Hall, 1982
  • Computer Vision, L. G. Shapiro and G. C. Stockman, Prentice-Hall, 2001
  • Machine Vision, R. Jain, R. Kasturi, and B.G. Schunck, McGraw-Hill, 1995
  • Computer and Robot Vision vol. 2, R. Haralick and L. Shapiro, Addison-Wesley, 1992
  • Object Recognition by Computer - The Role of Geometric Constraints, W.E.L. Grimson, MIT Press, 1990
  • The Eye, the Brain and the Computer, Fischler and Firschein, Addison-Wesley, 1987
  • Computer Vision, D. Ballard and C. Brown, Prentice-Hall, 1982
  • Vision, David Marr, Freeman, 1982
  • Digital Picture Processing, A. Rosenfeld and A. Kak, Academic Press, 1982

Grading Scheme:

  • Projects: 84%
  • Homeworks: 4%
  • Final Exam (oral): 12%

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: 10.0 and permission of the instructor

Course Code: COMP526
Course Title: Natural Language Processing

Instructor: Dekai Wu
Room: 3539
Telephone: X-6989
Email:
WWW page:
Area in which course can be counted: AI

Course Description:

  • Techniques for parsing, interpretation, context modeling, plan recognition, generation.
  • Emphasis on statistical approached, neuropsychological and linguistic constraints, large text corpora.
  • Applications include machine translation, dialogue systems, cognitive modeling, knowledge acquisition.

Background: COMP221

Course Code: COMP561
Course Title: Computer Networks

Instructor: Brahim Bensaou
Room:. 3525
Tel. No.: 2358 7014
Email:
WWW Page:
Area in which course can be counted: Networking & Computer Systems

Description:

  • Principles, design and implementation of computer communication networks;
  • network architecture and protocols, OSI reference model and TCP/IP networking architecture;
  • Internet applications and requirements;
  • transport protocols, TCP and UDP;
  • network layer protocols, IP, routing, multicasting and broadcasting;
  • local area networks;
  • data link and physical layer issues;
  • TCP congestion control, quality of service, emerging trends in networking.

Exclusion: COMP362

Course Code: COMP572
Course Title: Introduction to Combinatorial Optimization

Instructor: Mordecai Golin
Room: 3559
Telephone: X-6993
Email:
WWW page: http://cse.hkust.edu.hk/~golin/
Area in which course can be counted: TH

Course description:

  • An introduction to the basic tools of Combinatorial Optimization.
  • Includes: Network flow and the Max-Flow Min cut Theorem, Linear Programming, Matching, Spanning Trees and Matroids, Dynamic Programming and Basic Graph Algorithms

Course objective:

  • Upon completion of this course students will have been introduced to many of the most basic tools of combinatorial optimization and will be able to apply them towards designing efficient algorithms in their own research domains.

Text book:

  • Combinatorial Optimization: Algorithms and Complexity Christos H.
    Papadimitriou and Kenneth Steiglitz, Dover books, 1998

Grading Scheme: TBA

Background needed:

  • COMP271 or equivalent + Linear Algebra

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: permission of the instructor

Course Code: COMP621O
Course Title: Kernel Methods in Machine Learning

Instructor: James Kwok
Room: 3519
Telephone: 23587013
Email:
WWW page: http://cse.hkust.edu.hk/~jamesk/
Area in which course can be counted: AI

Course description:

  • Kernel methods (including the well-known support vector machines) is one of the most influential developments in modern machine learning.
  • Various kernel-based techniques are now playing an increasingly important role in both machine learning and other areas, including data mining, bioinformatics, electronic commerce, speech and language understanding, computer vision, computer graphics, information retrieval, and decision support systems.
  • This research-oriented course will introduce students to the basic concepts and some recent research topics in the field.
  • Applications to real-world problems will serve as examples.

Course objective:

  • The objective of this advanced topics course is to help research postgraduate students to keep abreast of some latest developments in modern machine learning, namely kernel methods.
  • The course will be focused on familiarizing the student with a number of practical kernel-based algorithms (such as support vector machines, kernel principal components analysis) and a number of techniques to construct kernels (such as string kernels, graph kernels, marginalized kernels).
  • Moreover, students will also learn novel applications to real-world problems that are made possible by the newly developed tools.
  • Students who have successfully finished this course should be ready to apply kernel techniques to their respective research areas.

Course outline/content (by major topics):

  • Major topics include kernel methods for supervised learning (e.g., support vector machines, support vector regression), unsupervised learning (e.g., kernel PCA, one-class support vector machines), semi-supervised learning and spectral methods. Kernel design.

Text book: No

Reference books/materials:

  • Many recent research papers

Grading Scheme: class participation + project

Background needed:

  • Background in machine learning or pattern recognition (equivalent to COMP 522 and COMP 527) preferred though not essential

Exclusion (if applicable): n/a

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: permission of the instructor

Course Code: COMP630I
Course Title: Topics in DB: Internet and Mobile Information Retrieval

Instructor: Dik Lun Lee
Room: 3534
Telephone: X-7017
Email:
WWW page: http://cse.hkust.edu.hk/~dlee/630/
Area in which course can be counted: Database

Course description:

  • Web-based search engines; peer-to-peer information retrieval; personalized search engines;
  • data access and dissemination of data in mobile wireless environments.

Course objective:

  • Students will acquire broad knowledge in information retrieval and search techniques on internet and wireless networks and develop indepth knowledge in a specific topic by carrying out a course project

Course outline/content (by major topics):

  • Advanced information retrieval, search and ranking algorithms, and relevance feedback
  • Peer-to-peer information retrieval
  • Query and page clustering by clickthrough analysis
  • Methods for personalizing search results for individual users
  • Accessing data on wireless broadcast and on-demand channels
  • Scheduling, indexing and caching mobile data
  • Open data access frameworks via wireless broadcast

Text book: None

Reference books/materials: Selected papers in the literature

Grading Scheme: class participation, course project and presentation

Pre-requisites/Background needed: Background in data management

Available for final year UG students to enroll: No

Course Code: COMP630K
Course Title: Advanced Topics on Database Research

Instructor: Dimitris Papadias
Room: 3503
Telephone: 23586971
Email:
WWW page: http://cse.hkust.edu.hk/~dimitris/
Area in which course can be counted: Databases

Course description:

  • This course introduces advanced concepts in database management systems, and teaches postgraduate students how to do high quality research on topics such as query processing and optimization, time series, high dimensional indexing, spatial and spatio-temporal data management, privacy preservation and security, mobile computing and location-based services.

Course objective:

  • Introduce students to the current state-of-the-art in Database Systems.
  • Provide background material on Database topics.
  • Identify trends in on-going Database research.
  • Teach students how to do high quality research in Database systems.
  • Prepare students for effective presentations.

Course outline/content (by major topics):

  • Advanced techniques for query processing and optimization.
  • Spatial and Spatio-temporal Databases
  • High Dimensional Indexing
  • Time Series and Similarity Search
  • Keyword Search in Databases
  • Data Streams and Sensor Networks
  • Aggregation Techniques
  • Privacy Preservation and Security
  • Mobile Computing and Location-based Services
  • Top-k and Skyline Queries

Text book:

  • There will be no textbook

Reference books/materials:

  • The class be based on recent research papers (mostly SIGMOD and VLDB)

Grading Scheme:

  • 40% student presentations
  • 30% survey paper
  • 30% implementation project

Pre-requisites/Background needed: None

Exclusion (if applicable): None

Available for final year UG students to enroll: No

Minimum CGA required for UG students: No requirement

Course Code: COMP641I
Course Title: Topics in Graphics: Visualization

Instructor: Dr. Huamin Qu
Email:
Area in which course can be counted: Vision & Graphics

Course description:

  • Visualization is a method of generating visual representations of complex multi-dimensional datasets using computer graphics and imaging techniques.
  • This course aims to provide graduate students with an overview of visualization and a survey of the latest advances in this rapidly expanding field.
  • Core visualization and computer graphics techniques and important scientific and commercial applications will be covered.
  • Topics include visual perception and color, 2D visualization, surface and volume visualization, vector-field visualization, visualization systems, and visualization of scientific, medical, engineering, business, and web datasets.

Course objective:

  • To provide a broad overview of visualization;
  • to survey the current hot research topics;
  • to explore new visualization techniques and applications.

Course outline/content (by major topics):

  • The visualization process
  • Human perception
  • Graphics and imaging techniques
  • Scientific visualization
  • Information visualization
  • Visualization systems
  • Case studies

Text book:

  • lecture notes and research papers

Reference books/materials:

  • The Visualization Toolkit: An Object Oriented Approach to 3D Graphics 3rd Edition by W. Schroeder, K. Martin, and B. Lorensen, Kitware, Inc., 2003
  • The Visual Display of Quantitative Information 2nd edition by E. Tufte, Graphics Press, 2001.

Grading Scheme:

  • Lab Assignments (30%)
  • Class Presentation (20%)
  • Final project (50%)

Background needed:

  • Basic computer graphics background equivalent to COMP 341

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: permission of the instructor

Course Code: COMP680G
Course Title: Selected Topics in Real-Time Embedded Systems

Instructor: Dr Zonghua Gu
Room: 3517
Telephone: 2358-7011
Email:
WWW page: http://cse.hkust.edu.hk/~zgu/
Area in which course can be counted: Networking & Computer Systems

Course description:

  • Real-time embedded (RTE) systems are prevalent in our modern society, ranging from simple microwave ovens controlled by an 8-bit processor, to complex spacecrafts containing thousands of processors.
  • Software development for RTE systems is often more difficult than for desktop applications, due to the presence of resource constraints and non-functional requirements, such as real-time, low-power and fault-tolerance.
  • This course focuses on techniques for modeling, analysis and implementation of RTE systems and software.

Course objective:

Course outline/content (by major topics):

  • Real-time scheduling
  • Real-time programming languages
  • Real-time operating systems and middleware
  • Model-based techniques
  • UML
  • Hardware/software codesign
  • Platform-based design
  • Component-based Approaches
  • Security
  • Hybrid Systems
  • Time-triggered Paradigms
  • Automotive Embedded software

Text book: None

Reference books/materials: None

Grading Scheme:

  • Participation (20%)
  • Class Presentation of papers (20%)
  • Project Proposal (5%)
  • Project Presentation (15%)
  • Project Report (40%)

Background needed:

  • UML, Java programming, Operating Systems

Exclusion (if applicable): None

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: Permission of the instructor

Course Code: COMP680J
Course Title: Self-Organizing Networks and Systems

Instructor: Professor Lionel Ni and Dr Yunhao Liu
Timetable: Mon, Wed 13:30-14:50
Room: 3501
Telephone: 2358-7009
Email:
WWW page: http://cse.hkust.edu.hk/~ni/
Area in which course can be counted: Computer Engineering

Course description:

  • In a self-organizing network or system, each node in the system communicates only with its immediate neighbors.
  • Neighbors relay messages to their neighbors in turn until the message reaches its destination.
  • Such a fully decentralized distributed system has many interesting features and has attracted attention to researchers in the design of large-scale distributed systems.
  • Examples of such systems include peer-to-peer networks, wireless sensor networks, and wireless mesh networks.

Course objective:

  • This course will study the mechanisms and environments of self-organizing networks and systems.
  • Many special features such as node autonomity, power consumption, localized transmission, node mobility, dynmaic routing, self-configuration, and self-healing will be studied.

Course outline/content (by major topics): Topics include peer-to-peer computing, wireless sensor networks and wireless mesh networks.

Text book: no

Reference books/materials: collection of research papers

Grading Scheme:

  • We will meet twice a week for a mixture of lectures and class discussions of assigned readings.
  • Grades will be based on class participation and a course project.
  • Each student will present one or more assigned papers and lead a class discussion.

Background needed: Permission of the instructor

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: Permission of the instructor

Course Code: COMP685C
Course Title: Security Protocols

Instructor: Cunsheng Ding
Room: 3518
Telephone: 2358-7021
Email:
WWW page: http://cse.hkust.edu.hk/faculty/cding/
Area in which course can be counted: Software & Applications

Course description:

  • This course gives an in depth coverage of security protocols for various applications such as computer networks, web services, and banking systems.
  • It also covers basic cryptographic primitives that are necessary in building security systems.
  • (This course will be delivered in lecture mode. Students will be asked to do presentations.)

Course objective:

  • After completion of this course, students will display a breadth of knowledge of security protocols, and master basic tools for building security systems.

Course outline/content (by major topics):

  • Introduction to cryptography, key agreement protocols, key distribution protocols, key management protocols, authentication protocols, identification protocols, secret sharing protocols, Secure Socket Layer, Transport Layer Security, Secure Shell, IP Security, Protocols for Secure electronic voting, protocols for electronic payment, protocols for wireless security, protocols for email security, zero knowledge protocols

Text book:

  • No textbook, lecture notes will be delivered.

Reference books/materials:

  • W. Stallings, Cryptography and Network Security: Principles and Practices, 3rd Edition, Prentice Hall, 2003.

Grading Scheme:

  • Assignments, quizzes, and course presentation.

Background needed:

  • Basics of computer networks

Available for final year UG students to enroll: Yes, with permission from the instructor

Course Code: COMP696T
Course Title: Independent Studies: Topics in Image and Video Research

No. of credits: 3
Instructor: Chi-Keung Tang
Room: 3561
Telephone: x8775
Email:

Course description:

  • Independent study in the state-of-the-art research in images and videos in the context of computer vision and graphics not covered by current course offerings

Course outline/content (by major topics):

  • To be arranged.

Available for final year UG students to enroll: No. Instructor's approval only

Course Code: COMP696U
Course Title: Independent Studies: Query Processing in Sensor Networks

No. of Credits: 3
Instructor: Dr. Qiong LUO
Quota: 4

Course description:

  • This course introduces the state of the art on query processing in sensor networks.

Course outline/content (by major topics):

  • In-network query processing architecture and implementation;
  • snapshot versus continuous queries; data acquisition and aggregation;
  • event detection; distributed storage and indexing; query optimization;
  • systems support for query processing.

Text book: None

Reference books/materials:

Grading Scheme:

  • 50% discussion, and 50% project.

Pre-requisites/Background needed:

  • Permission of the instructor.

Available for final year UG students to enroll: Yes.

Minimum CGA required for UG students:

  • Permission of the instructor.

Course Code: COMP696V
Course Title: Independent Studies: Software Testing and Debugging

No. of Credits: 3
Instructor: Dr. Shing-Chi Cheung
Quota: 3

Course description:

  • This independent project will explore the background and the state-of-the-art methodologies in software testing and debugging.
  • The course requires conducting experimentation based on existing test suites to evaluate and compare the effectiveness of various techniques.

Course outline/content (by major topics):

  • Infrastructure of Software Testing
  • Test Architecture
  • Test Methodology
  • Test Case Generation
  • Empirical Experimentation Techniques
  • Software Debugging
  • Statistical Debugging
  • Wireless Sensors Network Applications

Text book:

  • Model-based testing of reactive systems, Manfred Broy et al., Springer-Verlag, 2005
  • Experimentation in software engineering: an introduction, Claes Wohlin et al., Kluwer, 2000

Reference books/materials:

  • Related research papers published at the following venues.
  • International Conference on Software Engineering (ICSE)
  • Foundations of Software Engineering (FSE)
  • International Symposium on Software Testing and Analysis (ISSTA)
  • Automated Software Engineering (ASE)
  • IEEE Transactions on Software Engineering (TSE)
  • ACM Transactions on Software Engineering and Methodology (TOSEM)
  • Empirical Software Engineering (ESE)
  • Journal of Systems and Software (JSS)
  • IEEE Software

Grading Scheme:

  • Presentation (40%)
  • Report (60%)

Background needed:

  • Software engineering, C++, Java

Available for final year UG students to enroll: N/A.

Minimum CGA required for UG students: N/A

Course Code: COMP696W
Course Title: Independent Studies: P2P and wireless networks

No. of Credits: 3
Instructor: Dr. Gary Chan
Quota: 1 (instructor's approval is needed)

Course description:

  • A survey in p2p technologies including p2p wireless and IPTV/IP movie systems.
  • Approval of instructor is required.

Course outline/content (by major topics):

  • Student will read papers in the area and identify some possible future research direction.

Text book: N/A

Reference books/materials: Research papers

Grading Scheme:

  • 1 credit: a presentation at the end
  • 2 credits: a short report and a presentation
  • 3 credits: a survey and a presentation

Background needed: PG standing

Available for final year UG students to enroll: No.

Minimum CGA required for UG students: No.

Please visit https://www.ab.ust.hk/wcr/cr_class_staf_main.htm for the timetable and quota.

Archive of past courses

This web page was created by Gang Zeng on 21 July 2006.

Last modified on 25 August 2006.