Spring 2014 CS Course Listings

This file contains the Spring 2014 course listings for the Department of Computer Science and Engineering.

Archive of past courses

Course code: COMP5111
Course title: Fundamentals of Software Analysis
Instructor: Charles Zhang
Room: 3553
Telephone: 2358-6997
Email:
WWW Page: http://course.cse.ust.hk/comp5111

Area in which course can be counted: ST

Course description:
See course catalog.
Course objective:
The goal of this course is to introduce how various analysis techniques can be used to manage the quality of a software application. Students will acquire fundamental knowledge of program abstraction, features, verification, testing, refactoring, concurrency, reliability, aspect orientation, and fault analysis. The course will also discuss how to carry out the empirical experimentation for program analysis. Wherever applicable, concepts will be complemented by tools developed in academia and industry. This enables students to understand the maturity and limitations of various analysis techniques.

Course outline/content (by major topics):
Program Features, Program Abstraction, Static Analysis, Testing, Concurrency, Empirical Experimentation

Textbooks:

Reference books/materials:
* Paul Ammann and Jeff Offutt, Introduction to Software Testing, Cambridge University Press, 2008.
* Mauro Pezze and Michal Young, Software Testing and Analysis - Process, Principles, and Techniques, 1st edition, John Wiley & Sons, 2008.
* Claes Wohlin et al., Experimentation in Software Engineering, Kluwer Academic Publishers, 2000.
* Jeff Magee and Jeff Kramer, Concurrency - State Models & Java Programming, 2nd edition, John Wiley & Sons, 2006.

Grading scheme:
* Class Participation (10%)
* Assignments (50%)
* Final examination: (40%)

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: Permission of the instructor

Course code: COMP5211
Course title: Advanced Artificial Intelligence
Instructor: Fangzhen Lin
Room: 3511
Telephone: 2358-6775
Email:
WWW Page: http://cse.hkust.edu.hk/~flin/

Area in which course can be counted: AI

Course description:
This advanced AI course will cover the main concepts and techniques in AI. The major topics will be: problem solving, knowledge and reasoning, planning, uncertain knowledge and reasoning, learning, and robotics.

Course objective:
Students are expected to gain deep understanding of key concepts and techniques in AI, including heuristic search strategies for single agent problem solving as well as multi-agent strategic planning such as in game playing, knowledge representation and reasoning using both logic and probabilities, machine learning, and integrated agent design.

Course outline/content (by major topics):
1.Introduction.
2. Problem-solving.
3. Knowledge and Reasoning.
4. Planning.
5. Uncertain knowledge and reasoning.
6. Learning.
7. Communicating, perceiving, and acting.

Textbooks:
Stuart Russell and Peter Norvig. Artificial Intelligence: A Modern Approach Prentice Hall, 2003.

Reference books/materials:

Grading scheme:

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: Permission of the instructor

Course code: COMP5311
Course title: Database Architecture and Implementation
Instructor: Dimitris Papadias
Room: 3505
Telephone: 2358-6971
Email:
WWW Page:

Area in which course can be counted: DB

Course description:
This course introduces basic concepts and implementation techniques in database management systems: disk and memory management; advanced access methods; implementation of relational operators; query processing and optimization; concurrency control and recovery.

Course objective:
Introductory database class for graduate students. The students are expected to learn basic concepts and implementation techniques of relational databases and advanced RDBMS applications.

Course outline/content (by major topics):
The instructor will teach the majority of the classes. Students will form groups. Each group will choose a general database area and prepare a presentation.

Textbooks:
Textbook: Database System Concepts, 5th Edition. A. Silberschatz, H. Korth, and S. Sudarshan.

Reference books/materials:
Reference: Database Management Systems, 3rd Edition. Raghu Ramakrishnan and Johannes Gehrke.

Grading scheme:
Student Presentations 20%, Midterm 35%, Final 45%. Each presentation should be around 40 minutes. All students in each group should participate.

Available for final year UG students to enroll: No

Minimum CGA required for UG students: Permission of the instructor

Course code: COMP5421
Course title: Computer Vision
Instructor: C K Tang
Room: 3561
Telephone: 8775
Email:
WWW Page: http://cse.hkust.edu.hk/~cktang/

Area in which course can be counted: VG

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.

Background: COMP3211 knowledge in linear algebra.

Course objective:
Same as listed in the course catalogue/academic calendar

Course outline/content (by major topics):
1 Introduction
2 Image formation
3 Image filtering
4 Edge detection
5 Segmentation
6 Segmentation II
7 Texture
8 Projective geometry (handout)
9 Image warping
10 Stereo
11 Disparity by graph-cut
12 Surface from Stereo (Tensor voting)
13 Multiview stereo
14 Light
15 Photometric stereo
16 Optical flow
17 Structure from Motion

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

Reference books/materials:
* Three-Dimensional Computer Vision, O. Faugeras, MIT Press, 1993
* 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:
The breakdown is subject to change as a whole and adjustments on a per-student basis in exceptional cases.
This is the general breakdown we'll be using for Scheme 1:
Projects: 64%
Homeworks: 4%
Final Exam (Oral): 32%

Grading Scheme 2 targets at students in other research areas who need to fulfil the Vision/Graphics core requirement. The tentative breakdown for students signing up for Scheme 2 is as follow:
Project #1 and Papers Critique: 26%
Homeworks: 4%
Final Exam (Written): 70%

The two schemes will be described during the first and/or second lecture in September.

Computer projects and papers critique will be done in teams up to two students (three-student team is not permitted).

Homeworks are to be completed individually. Though you may discuss the problems with others, your answers must be your own.

Available for final year UG students to enroll: Yes.

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

Course code: COMP5531
Course title: Green Computing
Instructor: Jogesh Muppala
Room: 3510
Telephone: 2358-6978
Email:
WWW Page: http://course.cse.ust.hk/comp5531/

Area in which course can be counted: NE

Course description:
This course will exam "Green Computing" from a system perspective, meanwhile, students will study issues related to energy saving form multiple disciplines such as mechanical engineering, industrial ecology, and economics. We will explore energy efficient system designs ranging from datacenters to embed devices, such as sensor networks and RFID devices. We will perform Life Cycle Analysis on some of these systems, evaluating the carbon footprint of manufacturing, use, and disposal of each design. Exclusion(s): ENEG 5450.

Course objective:

Course outline/content (by major topics):

1. Introduction to Green Computing

2. Life Cycle Assessment (LCA)

3. Green Data Centers

4. Smart Grids

5. Sensor Networks and Green Technology

6. Green Networking

7. Green Storage


Textbooks:

Reference books/materials:

Grading scheme:

Research Paper Presentation 25 points

Survey/Research Paper/Project 75 points


Available for final year UG students to enroll: No

Minimum CGA required for UG students:

Course code: COMP5622
Course title: Advanced Computer Communications and Networking
Instructor: Qian Zhang
Room: 3533
Telephone: 2358 8766
Email:
WWW Page: http://cse.hkust.edu.hk/~qianzh

Area in which course can be counted: NE

Course description:
This course discusses the advanced principles in computer and communication networking. More particularly, the following topics will be addressed during this course, including multicast routing in the Internet; wireless and mobile computing; advanced topics for wireless networking; multimedia networking and quality of service; introduction to network security and wireless security; wireless sensor and senor networks.

Pre-requisites: COMP361/ELEC315/COMP561

Course objective:
Students taking this course will have a comprehensive training in all advanced and current aspects of computer networking. They will gain a thorough understanding of the theoretical issues, they will understand the basic principles behind some design choices and the will gain experience of some practical systems. They will understand the current evolution of the Internet and the future trends in the development of the field of networking, which will equip them with the necessary background to start their research in any area of networking.

Course outline/content (by major topics):
1) Review of the basic principles of computer networking
2) Broadcasting and Multicasting
3) Basis about Wireless and Mobile Computing
4) Advanced topics for wireless networking (multi-channel, wireless TCP, multi-hop networks)
5) Multimedia Networking and Quality of Service Provision
6) Network Security and Wireless Security
7) Wireless sensor and sensor networks
8) Student Presentation

Textbooks:
Computer Networking: A Top-Down Approach (6th Edition), James F. Kurose and Keith W. Ross.
A collection of papers from journals, conference proceedings, and website need to be read.

Reference books/materials:
TBA

Grading scheme:
Homework 20 points
Paper Presentation 20 points
Project Report 20 points
Final Exam 40 points

Available for final year UG students to enroll: Yes.

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

Course code: COMP5713
Course title: Computational Geometry
Instructor: Timothy Chan
Room: 3548
Telephone: 2358 6972
Email:
WWW Page: http://course.cse.ust.hk/comp5713

Area in which course can be counted: TH

Course description:
An introductory course in Computational Geometry. Algorithms for manipulating geometric objects.

Background: COMP 3711

Course objective:
To introduce postgraduate students to the area of computational geometry, the fundamental results and algorithms in the area.

Course outline/content (by major topics):
Topics include Convex Hulls, Point-Line Duality, Voronoi Diagrams and Delaunay Triangulations, Low-Dimensional Linear Programming, Randomized Algorithms, Line Segment Intersection, Arrangements, Point Location, Polygon Triangulation, Range Searching.

Textbooks:
M. de Berg, O. Cheong, M. van Kreveld, and M. Overmars, Computational Geometry: Algorithms and Applications, 3rd Edition, Springer.

Reference books/materials:

Grading scheme:
Written assignments, midterm, and final examination.

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students: B

Course code: COMP6511A
Course title: Large-Scale Distributed Systems
Instructor: Lin Gu
Room: 3562
Telephone: 2358 6991
Email:
WWW Page: (TBA)

Area in which course can be counted: NE

Course description:
Cloud computing relies on the large-scale distributed systems running in datacenters strategically positioned around the globe. Such highly provisioned computing systems require that we re-design many components of the computing systems, including hardware, operating systems, storage abstractions, data models, programming frameworks, development utilities, user interfaces, and software engineering practice, to deliver computation at such a large scale. Many technologies have been constructed to fulfill this mission. This seminar course studies the organization of cloud computing systems and survey research problems in this area. The class meets twice a week for a mixture of lectures and class discussions of assigned readings. In addition, a course project based using c0, a new distributed programming language, provides opportunities for hands-on experience with real-world problems.

Course objective:
This course aims to inspire students to learn the design and implementation of cloud computing systems, and study the design issues and research questions in large-scale distributed systems. Students shall also acquire hands-on experience in developing programs that run on a number of distributed compute nodes.

Course outline/content (by major topics):
Datacenter organization, distributed operating systems, storage abstractions, large-scale in-memory computation, data models, networks for the cloud, distributed programming, and software engineering practice

Textbooks:
No

Reference books/materials:

Grading scheme:
(TBA)

Available for final year UG students to enroll: Yes

Minimum CGA required for UG students:

Please visit here for the timetable and quota.

Archive of past courses

Last modified by Zhiyang Su on 2014-01-20.