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ENGG 5105 - Computer and Network Security

Enrollment Information
Enrollment Requirement For students in MSc Computer Science or MPhil-PhD programmes under Faculty of Engineering or UG Computer Science or UG Computer Engineering; Not for students who have taken CMSC5726 or CSCI5470
Description
 
This course aims to introduce important topics in computer and network security from an applied perspective. Topics include: (i) applied cryptography (e.g., cryptographic primitives, programming with OpenSSL), (ii) network security (e.g., unauthorized accesses, large-scale network attacks, firewall & intrusion detection systems), (iii) web security (e.g., HTTP session management and web attacks), and (iv) system security (e.g., buffer overflow, passwords, file system security). The course also discusses latest applied security topics depending on the current research trends.
Advisory: Students are expected to have taken CSCI3150 or ESTR3102, and CSCI4430 or CENG4430 or IERG3310

ENGG 5202 - Pattern Recognition

Enrollment Information
Enrollment Requirement For ELEG major and minor undergraduate as elective course;For students in MPhil-PhD programmes under Faculty of Engineering;Not for students who have taken ELEG5503 or ELEG5760
Description
 
This course provides an introduction to the important concepts, theories and algorithms of pattern recognition. The topics cover Bayesian decision theory, maximum likelihood and Bayesian parameter estimation, support vector machine, boosting, nonparametric pattern recognition methods, and clustering. It also includes applications of pattern recognition in different fields. Students taking this course are expected to have the background knowledge of calculus, linear algebra, probability and random process as a prerequisite. Pre-requisite: ELEG3410 or with the consent of the instructor.

ENGG 5281 - Advanced Microwave Engineering

Enrollment Information
Enrollment Requirement For ELEG major and minor undergraduate as elective course;For students in MPhil-PhD programmes under Faculty of Engineering or MSc Electronic Engineering;Not for students who have taken ELEG5205 or ELEG5310
Description
 
This course is designed to introduce the Advanced Microwave Engineering. Topics will be selected from the following: Linearization techniques for RF power transmitters, high frequency circuit packaging, microwave filter design, LTCC/MCM technology, computer-aided design of microwave circuits, electromagnetic simulation.

ENGG 5282 - Nanoelectronics

Enrollment Information
Enrollment Requirement For students in MSc Electronic Engineering or MPhil-PhD programmes under Faculty of Engineering;Not for students who have taken ELEG5500
Description
 
This course is a review of semiconductor physics. The course content covers the following topics. Electrons in nanostructures: density of states, quantum confinement, transport properties, nanocontacts, Coulomb blockade. Nanoscale fabrication and synthesis: lithography, nanopatternning, epitaxy and heterostructure, self-assembly, other techniques. Nanoscale characterization: scanning probe microscopy and other microscopic techniques, nanoscale electrical measurements. It also introduces nanoscale devices such as nano-MOSFETs; carbon nanotube devices, nanowire- and nanoparticle-based devices, organic thin film devices, molecular electronic devices, their applications, and commercialization. Pre-requisite: ELEG2510 or ELEG3510 or ELEG4510 or with the consent of the instructor.

ENGG 5291 - Fiber Optics: Principles and Technologies

nrollment Information
Enrollment Requirement For students in MSc Electronic Engineering or MPhil-PhD programmes under Faculty of Engineering;Not for students who have taken ELEG5610
Description
 
This course is an overview of fiber communication technology. This course content covers fiber transmission impairments, introduction to nonlinear optics, second order and third order nonlinear phenomena, lightwave propagation in nonlinear media, optical signal processing in communications and specialty fibers.

ENGG 5301 - Information Theory

Enrollment Information
Enrollment Requirement For all students in Engineering Faculty;Exclusion: IERG5154
Course Attributes
Blended-mode class available
Description
 
Introduction. Shannon's information measures. Entropy rate of a stationary process. The source coding theorem. Kraft inequality. Huffman code. Redundancy of a prefix code. The channel coding theorem. Rate-distortion theory. Universal data compression.

Blended-mode class section is available for this course. Please refer to the "Class Notes" of the blended-mode class section for details.

Advisory: Students are expected to have fundamental probability concepts.

ENGG 5303 - Advanced Wireless Communications

Enrollment Information
Enrollment Requirement For all students in Engineering Faculty
Exclusion: IERG6270 or IERG5100
Description
 
This course provides an extensive introduction to basic principles and advanced techniques in the physical layer of wireless communications. Topics to be covered include channel coding, MIMO and
space-time processing, OFDM and multicarrier systems, spread spectrum and CDMA, channel capacity, opportunistic scheduling and diversity schemes.

Advisory: A prior undergraduate level course in wireless communication is highly recommended.

ENGG 5402 - Advanced Robotics

Enrollment Information
Enrollment Requirement For students in MSc Mechanical and Automation Engineering or MPhil-PhD programmes under Faculty of Engineering; or For undergraduate students in Mechanical and Automation Engineering
Description
 
This course provides a comprehensive overview of robotics for postgraduate level study. The course covers the fundamental concepts and methods to analyze, model, and control of robotic mechanisms. Specific topics include kinematics, inverse kinematics, dynamics, trajectory generation, individual and multivariable control, interaction force control, and sensors. Students will also involve in hands-on programming project to reinforce the basic principles developed in lectures as well as develop robot algorithm implementation skillsets. The course will also expose students to the latest and advanced developments in robotics such as medical robotics, dynamic parameter identification.

ENGG 5403 - Linear System Theory & Design

Enrollment Information
Enrollment Requirement For students in MSc Mechanical and Automation Engineering or MPhil-PhD programmes under Faculty of Engineering; or
For undergraduate students in Mechanical and Automation Engineering;Not for students who have taken MAEG5725
Description
 
Linear system theory and design is the core of modern control approaches, such as optimal, robust, adaptive and multivariable control. This course aims to develop a solid understanding of the fundamentals of linear systems analysis and design using the state space approach. Topics covered include state space representation of systems; solution of state equations; stability analysis; controllability and observability; linear state feedback design; observer and compensator design, advanced multivariable control systems design, decoupling and servo control. This course is a must for higher degree students in control engineering, robotics or servo engineering. It is also very useful for those who are interested in signal processing and computer engineering.

ENGG 5404 - Micromachining and Microelectromechanical Systems

Enrollment Information
Enrollment Requirement For students in MSc BMEG and MAEG; or MPhil-PhD programmes under Faculty of Engineering; or
For undergraduate students in BMEG or MAEG;Not for students who have taken MAEG5750
Description
 
This course provides a broad overview of microfabrication and microelectromechanical systems. Topics include introduction to basic micromaching techniques such as photolithography; isotropic and anisotropic wet etching; dry etching; physical and chemical vapor deposition; electroplating; metrology; statistical design of experiments; MEMS release etching; stiction; and MEMS device testing. The course also reviews important microsensors, microactuators and microstructures. Topics include accelerometers; pressure sensor; optical switches; cantilever beams; thin-film stress test structures and bulk micromaching test structures. Lastly, the course introduces the fundamentals of central dogma of molecular biology; cell and tissue biology; and principles of transduction and measurements of molecules, cells and tissues.

ENGG 5501 - Foundations of Optimization

Enrollment Information
Enrollment Requirement For students in MPhil-PhD programmes under Faculty of Engineering;Not for students who have taken SEEM5520
Description
 
In this course we will develop the basic machineries needed for formulating and analyzing various optimization problems. Topics include convex analysis, linear and conic linear programming, nonlinear programming, optimality conditions, Lagrangian duality theory, and basics of optimization algorithms. Applications from different fields, such as computational economics and finance, combinatorial optimization, and signal and image processing, will be used to complement the theoretical developments. No prior optimization background is required for this class. However, students should have a workable knowledge in multivariable calculus, basic concepts of analysis, linear algebra and matrix theory.

ENGG 5601 - Principles of Biomechanics and Biomaterials

Enrollment Information
Enrollment Requirement For MSc Biomedical Engineering students; or For MPhil-PhD students under Faculty of Engineering;Not for students who have taken BMEG5150
Description
 
This course focuses on biomechanics (biostatics, biodynamics, mechanics of biological solids), biomaterials (metals, ceramics, synthetic polymers, natural polymers, composites; characterization of biomaterials; biomaterial scaffolds for regenerative medicine) & clinical applications in the musculoskeletal system (including, sports, traumatology, and rehabilitation), cardiovascular system, and dentistry.

ENGG 5781 - Matrix Analysis and Computations

Enrollment Information
Enrollment Requirement For MPhil-PhD Engineering Students
Description
 
Matrix analysis and computations are widely used in engineering fields—such as machine learning, computer vision, systems and control, signal and image processing, optimization, communications and networks, and many more—and are considered key fundamental tools. This course covers matrix analysis and computations at an advanced or research level. It consists of several parts. The first part focuses on various matrix factorizations, such as eigendecomposition, singular value decomposition, Schur decomposition, QZ decomposition and nonnegative factorization. The second part considers important matrix operations and solutions such as matrix inversion lemmas, linear system of equations, least squares, subspace projections, Kronecker product, Hadamard product and the vectorization operator. Sensitivity and computational aspects are also studied. The third part explores presently frontier or further advanced topics, such as matrix calculus and its various applications, tensor decomposition, and compressive sensing (or managing undetermined systems of equations via sparsity). In every part, relevance to engineering is emphasized and applications are showcased.

Each M.Phil. or Ph.D. student is required to complete the graduate-level lecture courses offered by the Department, or by other Divisions as prescribed by the supervisor or the Division Head. M.Phil. student is required to complete a minimum of 12 units and Ph.D. student is required to complete a minimum of 21 units. At least one faculty core course must be taken. Students have to obtain at least a B for the Faculty core course to satisfy the core course requirement.

The following table lists the graduate-level lecture courses in Electronic Engineering. About six of them are offered each year. The latest teaching time table can be found in the Graduate School web page. (http://www.gs.cuhk.edu.hk/page/TeachingTimetable)

Course Code Course Title Units
ELEG5020 Advanced Topics in Integrated Circuits and Systems 3
ELEG5030 Advanced Topics in Wireless Communications 3
ELEG5040 Advanced Topics in Signal Processing 3
ELEG5050 Advanced Topics in Solid State Technology 3
ELEG5060 Applied Functional Analysis and Approximation Theory 3
ELEG5280 Analog-Digital ASIC Design 3
ELEG5301 Photonic Integrated Circuits 3
ELEG5491 Introduction to Deep Learning 3
ELEG5502 Video Coding Technology 3
ELEG5520 Advanced Topics in Optoelectronics 3
ELEG5550 Micro- and Nano-Fabrication Laboratory 3
ELEG5600 Advanced Perception for Intelligent Robotics 3
ELEG5620 Electronic Engineering Seminar 3
ELEG5723 CMOS Analog IC Design 3
ELEG5726 Power Management Technology 3
ELEG5732 RF Circuits and Systems 3
ELEG5741 Digital Processing of Speech Signals 3
ELEG5753 Flexible Electronics and Solar Cell Technology 3
ELEG5754 Solid-state Sensors and Lighting Systems 3
ELEG5755 Optical Communication and Interconnects 3
ELEG5759 Innovation, Technology and Management in Modern Engineering 3
ELEG5761 Power Converters and Their Grid Applications 3
ELEG5762 Neuromorphic Hardware for Brain-like Computation 3

"Faculty Core Course List"

Course Code Pairing course Course Title
ENGG 5101 CNEG 5410 Advanced Computer Architecture
ENGG 5103 CSCI 5180 Techniques for Data Mining
ENGG 5104 CSCI 5280 Image Processing and Computer Vision
ENGG 5105 CSCI 5470 Computer and Network Security
ENGG 5106 CSCI 5250 Information Retrieval and Search Engines
ENGG 5108 -- Big Data Analytics
ENGG 5189 CSCI 6200 Advanced Artificial Intelligence
ENGG 5202 ELEG 5503 Pattern Recognition
ENGG 5281 ELEG 5205 Advanced Microwave Engineering
ENGG 5282 ELEG 5500 Nanoelectronics
ENGG 5291 ELEG 5610 Fiber Optics: Principles and Technologies
ENGG 5301 IERG 5154 Information Theory
ENGG 5302 IERG 5300 Random Processes
ENGG 5303 IERG 6270 Advanced Wireless Communications
ENGG 5383 IERG 5240 Applied Cryptography
ENGG 5392 IERG 5040 Lightwave System Technologies
ENGG 5402 MAEG 5010 Advanced Robotics
ENGG 5403 MAEG 5020 Linear System Theory and Design
ENGG 5404 MAEG 5050 / BMEG 5120 Micromachining and Microelectromechanical Systems
ENGG 5405 MAEG 5100 Theory of Engineering Design
ENGG 5501 SEEM 5520 Foundations of Optimization
ENGG 5601 BMEG 5150 Principles of Biomechanics and Biomaterials
ENGG 5781 -- Matrix Analysis and Computations

*The course list will be reviewed each year

Objective
Electronic engineering is a fast evolving interdisciplinary field. This course consists of the most up-to-date research topics presented by active researchers and experts in the field and strikes a balance between discussions of hardware and software development in electronic engineering. There will be 26 seminars in total, and each seminar contains a 45-minute presentation followed by a 25-minute discussion session. The students are required to attend at least 50% of the seminars and write one report on their learning from one or two specific seminars.

Syllabus
Seminars in the areas of image and video processing, digital signal processing and speech technology, microwave and wireless communications, robotics, perception and AI, photonics and optical communications, solid state electronics and VLSI, ASIC and energy conversion.

Learning Outcome
Upon successful completion of the course, students will be able to

  1. Stay abreast of latest technological developments in the field of electronic engineering
  2. Acquire knowledge of research topics related to electronic engineering
  3. Acquire, enhance, and practice presentation skills
  4. Develop skills in analytical and reflective thinking

 

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Objective & Syllabus
This course introduces the advanced topics in perception for intelligent robotics. It covers fundamental concepts and techniques of machine vision, robotic image and video processing, sensor fusion for semantic mapping and exploration, pattern recognition, learning and deep neural networks, robotic scenario intelligence, perception and anticipation of human behaviors, and advanced robotic trajectory and task planning. Case studies of successful medical and service robotics are discussed. In the course project, students are required to propose, design and implement a robotic system with intelligent perception to map and explore dynamic environment and interact with human subjects.

Learning Outcome
Upon successful completion of the course, students will be able to

  1. explain the roles of hardware and software in an intelligent robotic system;
  2. explain the building elements of a modern intelligent robotic system;
  3. apply advanced algorithms to navigate robots in dynamic environment and to carry out robotic interactions with human subjects;
  4. perform experiment studies on intelligent robot hardware and software;
  5. design and implement a robotic system for intelligent mapping and exploration of dynamic environment and interaction with human subjects.

 

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The Chinese University of Hong Kong

Department of Electronic Engineering

 

Fast track PhD application for Fall 2020

Due to the COVID-19 (Coronavirus), the study aboard plans of some outstanding students who are holding an admission offer from top overseas universities have been affected.

To help outstanding students to commence their PhD studies as planned, CUHK EE Department now opens a fast track PhD application for Fall 2020.

Full postgraduate studentships will be provided.

The application result will be announced within two weeks.

 

Application deadline: 30 June 2020

Potential candidates may submit the following application materials to This email address is being protected from spambots. You need JavaScript enabled to view it.:

-        CV, transcripts

-        TOEFL or IELTS report

-        PhD offer letter from overseas universities

-        Potential supervisor and research interest

Email Subject: [Name] + CUHK EE 2020 Fall Fast Track PhD Application

 

 

香港中文大学电子工程学系

2020秋博士入学申请快速通道

 

为支持优秀学子们在疫情或海外签证影响下，能如期入学开始博士研究，本系现开通快速通道，欢迎申请！

提供全额奖学金，承诺两周内回复申请结果。

 

申请截止日期：2020年6月30日

如何申请？准备如下材料发送到 This email address is being protected from spambots. You need JavaScript enabled to view it. 即可：

  • 简历、成绩单
  • 托福或雅思成绩
  • 海外博士录取通知书
  • 意向导师和研究兴趣

邮件标题请使用如下格式：

[Name] + CUHK EE 2020 Fall Fast Track PhD Application

  1. Research Area
  2. 研究領域
  3. ELEG5755 - Optical Communication and Interconnects
  4. ELEG5754 - Solid-state Sensors and Lighting Systems
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