Postgraduate Courses

Undergraduate courses marked with [BLD] or [SPO] may be offered in the mode of blended learning or self-paced online delivery respectively, subject to different offerings. Students should check the delivery mode of the class section before registration.

• ELEC 5010

  Introduction to the Design & Implementation of Micro-Systems

  [3 Credit(s)]
  Exclusion(s)

  MECH 5950

  Description

  Introduction to the concept of micro-systems. Dimensional scaling and its implications. Multi-physics modeling. Micro-fabrication techniques. Introduction to Coventor, a numerical simulation package for micro-systems. The design, implementation and testing of a micro-device.
• ELEC 5020

  Optical Materials and Applications

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910F

  Description

  The course introduces optical properties of isotropic (dielectric, metallic, semiconducting) and anisotropic (crystalline, liquid crystalline) materials and the influence of external fields (electric, magnetic, strain). The optical properties are discussed in various applications (lenses, mirrors, gratings, wave plates, modulators, liquid crystal devices).
• ELEC 5040

  Advanced Analog IC Analysis and Design

  [3 Credit(s)]
  Exclusion(s)

  EESM 5120

  Background

  ELEC 4420 and ELEC 4510

  Description

  Noise analysis; Advanced op-amp design techniques; Analog VLSI building blocks: multipliers, oscillators, mixers, phase-locked loops, A/D and D/A converters; Passive filter design; Frequency scaling; Active filter design.
• ELEC 5050

  Advanced CMOS Devices

  [3 Credit(s)]
  Prerequisite(s)

  ELEC 3500

  Description

  Principles and characteristics of semiconductor devices found in State-of-the-Art ICs. Emphasis is on deep-submicron MOS device design, characterization and modeling. Important issues such as short channel effects, high-field behavior, hot carrier effects, reliability and device scaling for present and future technology will be covered.
• ELEC 5070

  Microelectronics Fabrication Technology

  [3 Credit(s)]
  Description

  Process technologies in IC fabrication: epitaxial growth; chemical-vapor and physical-vapor deposition of films; thermal oxidation; diffusion; ion implantation; microlithography; wet/dry etching processes; process integration of MOS and bipolar technologies.
• ELEC 5080

  Integrated-Circuit Fabrication Laboratory

  [4 Credit(s)]
  Prerequisite(s)

  ELEC 5070

  Description

  Laboratory course requiring hands-on work in fabricating MOS transistors. Process modules including photolithography, dry etching, wet etching, metal sputtering, oxidation, diffusion and low-pressure chemical-vapor deposition will be covered. Student will also learn to characterize the fabricated devices.
• ELEC 5090

  Advanced Photonics Technologies

  [3 Credit(s)]
  Description

  A brief review of modern optics theories, Fourier optics based devices and systems, fundamentals of laser physics, optoelectronics, nonlinear optics and laser spectroscopy.
• ELEC 5110

  Nanoelectronic Materials for Energy Technologies

  [3 Credit(s)]
  Co-list with

  ENEG 5200

  Exclusion(s)

  ENEG 5200

  Background

  ELEC 3500

  Description

  Conventional and unconventional fabrication of nanostructures including electron beam lithography, nanoimprint, chemical synthesis, self-assembly, etc.; size dependent electronic and optoelectronic properties of nanomaterials; large-scale assembly and integration of nanomaterials for electronics; energy harvesting and storage devices using nanoelectronic materials.
• ELEC 5120

  Semiconductor Power and Energy Conversion Technologies

  [3 Credit(s)]
  Co-list with

  ENEG 5250

  Exclusion(s)

  ENEG 5250

  Description

  Analysis of power semiconductor device technologies in the context of electric power conversion and transmission; emphasis on the understanding of the critical roles of semiconductor device technologies in power and energy conversion. The mainstream silicon and emerging semiconductor power devices technologies; material properties, device structure design, advanced fabrication techniques, and device characteristics. Critical device-circuit interaction issues and basic power electronics circuits will be covered focusing on the role of these circuits in electric power conversion and transmission.
• ELEC 5130

  RF Microsystems: Devices and Applications

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910B

  Description

  Students will receive the following knowledge: Electromagnetic fields & waves, transmission line theory, Smith Chart, S-parameters, and Network Analysis; RF wireless communication systems; Properties of passive components; Impedance Matching network, RLC networks, and 2-port parameters; Microwave measurement and calibration; Simulation methods for EM passive devices: HFSS & PathWave Advanced Design System (ADS); Micron passive acoustic wave devices: resonators, filters, delay lines; Simulation methods for multi-physic devices: COMSOL; MEMS technologies for RF microsystems. This course discusses methodologies to synthesize and model the operation of several key passive components currently employed in commercial Radio Frequency (RF) microsystems. The operation, design methodologies, and equivalent circuit representations relative to RF devices will be presented.
• ELEC 5140

  Advanced Computer Architecture

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910K

  Background

  Background knowledge in ELEC 2300 (Computer Organization) or COMP 2611 (Computer Organization)

  Description

  The course introduces the important building blocks in modern computing systems including superscalar processor pipeline, memory hierarchies, network design in the multicore‐processors. The design techniques, evaluation metrics and optimization techniques will be discussed in detail with the example of real computer systems. The students will gain not only theoretical knowledge through lectures, but also hands‐on experiences through projects.
• ELEC 5150

  21st Century Solid-State Devices: From Principles to Applications

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910Z

  Description

  This course provides a comprehensive survey of solid-state devices developed after 2000. Topics include advanced thin-film device physics, next-generation transistors, perovskite and organic photovoltaics (including tandem configurations), memristors, in-memory computing, and sensors/organic electrochemical transistors. The course places a strong emphasis on quantitative electrical characterizations and luminescent measurement techniques, model-based reasoning, reliability and variability assessments, and device-system co-design, particularly for applications in displays, imaging, and energy.
• ELEC 5160

  Digital VLSI System Design and Design Automation

  [3 Credit(s)]
  Prerequisite(s)

  ELEC 3410

  Exclusion(s)

  EESM 5020

  Background

  ELEC 2200

  Description

  Structured design styles; specification, synthesis and simulation using Hardware Descriptive Language (HDL); Structural chip design and system design; Circuit design of system building blocks: arithmetic unit, memory systems; clocking and performance issues in system design; Design-Automation tools and their applications.
• ELEC 5170

  Advanced AI Chips and Systems

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910H

  Description

  This is an introductory course to advanced processor architecture for AI computing. The topics covered include AI algorithm basics, processing element, dataflow, memory system, software-hardware co-design for AI processors. This course will also introduce benchmarking and recent advances of AI processors.
• ELEC 5180

  RF/Microwave Circuit Design and Measurement

  [4 Credit(s)]
  Background

  ELEC 3100, ELEC 3400, ELEC 3600 and ELEC 4420

  Description

  Introduction to techniques for analyzing, engineering and testing of circuits for RF/microwave frequencies using CAD tools. The lab provides hands-on CAD/simulation, building and testing of low-noise amplifier, mixer, VCO, filter, IF AGC, detectors and other circuits discussed in lecture.
• ELEC 5210

  Advanced Topics in Nanoelectronics

  [3 Credit(s)]
  Background

  ELEC 4510

  Description

  Introduction to state-of-the-art development in the broad area of nanoelectronics, including concepts and devices for spin electronics and quantum information science. Students are expected to demonstrate the capability of applying fundamental principles to understand advanced electronic devices through hands-on homework projects.
• ELEC 5240

  Advanced Display Technologies

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910V

  Background

  Basic understanding of calculus and algebra

  Description

  Introduction of the human visual system, Colorimetry and photometry, Introduction of the modern TFTs, Modern AMLCD, AMOLED, Fluorescence and phosphorescence, Introduction of Electrophoretic displays, Color electrophoretic displays, Nano-material for displays, Electroluminescence and Photoluminescence, Quantum dot, Quantum rods, State-of-the-art development in the area of display technology: High-resolution displays (4k, 8k, and 10k), Local backlight dimming, Introduction to AR/VR display solutions, Holographic displays, Flexible displays etc.
• ELEC 5280

  High Frequency Circuit Design

  [3 Credit(s)]
  Background

  ELEC 3100, ELEC 3400, ELEC 4180 and ELEC 4630

  Description

  High frequency circuit design for wireless applications. S-parameters, front-end amp, VCO, PLL, power amplifier, and integration issues will be covered.
• ELEC 5300

  Stochastic Processes

  [3 Credit(s)]
  Background

  ELEC 2600

  Description

  Borel/sigma fields. Sequences of random variables and convergence. Spectral factorization. Karhunen-Loeve Expansion. Stationarity, ergodicity and spectral estimation. Mean square estimation and Kalman filtering. Entropy. System identification.
• ELEC 5360

  Principles of Digital Communications

  [3 Credit(s)]
  Exclusion(s)

  EESM 5536

  Background

  Probability theory

  Description

  The aim of this course is to provide an in-depth treatment of the theoretical basis, analysis, and design of digital communication systems. The first half of the course will focus on the theoretical foundations of a basic digital communication system, including source coding, modulating and channel coding, and introductory information theory. The second half will deal with advanced techniques including orthogonal frequency division multiplexing (OFDM), multi-antenna communications, spread-spectrum communications, and cooperative communications.
• ELEC 5380

  Neural Data Representation, Generation, and Compression

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910C

  Background

  General knowledge about source coding, machine learning, and deep learning.

  Description

  This course introduces state-of-the-art development in the interplay between information theory, data compression, and machine learning, including source coding theory, deep generative models, neural data compression, representation learning, compressibility and learnability, and neural network compression.
• ELEC 5460

  Stochastic Optimization for Wireless Systems and Federated-Learning

  [3 Credit(s)]
  Background

  ELEC 4110 or equivalent

  Description

  Stochastic Optimization plays a critical role in radio resource optimization of wireless networks, optimal control theory as well as financial engineering (portfolio optimization). This course will focus on the stochastic optimization theory and the application to the design and optimization of next generation wireless systems and federated learning applications. Topics covered include (A) Physical Layer Modeling: review of information theory for wireless fading channels, MIMO spatial diversity and spatial multiplexing, (B) Theory of Stochastic Optimization: classifications and motivating examples of stochastic optimizations [Type I stochastic Optimization and Type II stochastic optimization problems], theory of Stochastic Approximation, Stochastic Gradient, (C) Applications of Type I SO: Robust optimizations and Federated Learning: (D) Applications of Type II SO: Markov Decision Process, Stochastic Stability and Delay-optimal wireless resource control.
• ELEC 5470

  Convex Optimization

  [3 Credit(s)]
  Background

  Linear algebra (also basic digital communications and basic signal processing)

  Description

  Convex optimization theory with applications to communication systems and signal processing: convex sets/functions/problems; Lagrange duality and KKT conditions; saddle points and minimax problems; numerical algorithms; primal/dual decomposition methods. Applications: filter design; robust beamforming; power control in wireless systems; design of MIMO systems; GP duality in information theory; network utility maximization. For PG students in second year or above.
• ELEC 5510

  Switch Mode Power Converters

  [3 Credit(s)]
  Background

  ELEC 2100 AND ELEC 3400

  Description

  DC-DC conversion: topologies, continuous and discontinuous conduction modes, steady state analysis, loop gain analysis and relevant mathematical tools, stability and compensation; AC-DC conversion: power factor correctors.
• ELEC 5520

  Power Management Integrated Circuit Design

  [3 Credit(s)]
  Background

  ELEC 4420 and ELEC 4430

  Description

  Integrated circuit techniques for power management components such as voltage references, linear voltage regulators, low dropout regulators, switch mode power converters and switched-capacitor power converters.
• ELEC 5530

  Mixed-Signal Integrated Bio-Sensory Circuit Design

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910C

  Background

  ELEC 4420

  Description

  The course aims to systematically introduce major issues of mixed-signal circuit designs and their applications in bio-medical and sensory systems. The first half course is dedicated to mixed-signal IC design. The course starts with 2 review classes on OPAMP design, filter design and circuit noise. Then, the course covers topics on pipelined ADC, Sigma-delta ADC, and SAR ADC. The second half course is dedicated to sensory and bio-medical IC design. The topics include bio-potential detection, implants, DNA detection, CCD, CMOS imaging, and CT/SPECT.
• ELEC 5550

  Electronic Design Automation for VLSI Design

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910D

  Background

  Basic knowledge on data structure and algorithms and digital logic design

  Description

  The course introduces Electronic Design Automation (EDA) techniques for VLSI digital IC design. The modern RTL to GDS-II design flow and related tools will be explained in detail. Classical automated algorithms adopted in logic synthesis, floorplanning, placement, clock tree synthesis (CTS), routing, etc. will be covered. Simulation and optimization techniques of key IC design objectives, including recent research on AI-assisted EDA, will be presented.
• ELEC 5600

  Linear-System Theory

  [3 Credit(s)]
  Background

  ELEC 2100, MATH 2350 and MATH 2352

  Description

  Introduces modern system theory, with applications to control, signal processing and related topics. Basic system concepts, state-space and I/O representation, properties of linear systems, controllability, observability, minimality, transfer-function matrices, state and output feedback, stability, observers, optimal regulators.
• ELEC 5621

  Introduction to Biorobot: From Nature to Engineering

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910G

  Description

  Biorobotics is an interdisciplinary field that encompasses biomedical engineering, cybernetics, robotics, and more. This course aims to provide an introduction to the fundamental concepts and knowledge of biorobots. It will cover the description and analysis of biorobots with various types of nature-inspired locomotion and behavior. Additionally, it will explore different architectures and scales of biorobots; and discuss advanced techniques and interdisciplinary knowledge required for their development.
• ELEC 5630

  First Principles of Computer Vision

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910A

  Description

  This course focuses on the fundamental mathematical and physical principles of computer vision. It begins by introducing the physical imaging process, encompassing crucial subjects such as color, polarization, radiometry, reflectance models, and photometric methods. Subsequently, it explores the realm of geometric multi-view vision, encompassing topics like features, multi-view stereo, optical flow, structure-from-motion, visual SLAM, and NeRF. Finally, the course delves into the domain of learning-based methods including classification, segmentation, detection, and diffusion models.
• ELEC 5640

  Robot Manipulation

  [3 Credit(s)]
  Co-list with

  MECH 5561

  Exclusion(s)

  MECH 5561

  Description

  Extensive introduction to robot manipulation theory from a geometric viewpoint. Rigid-body kinematics; spatial and body representation of rigid-body velocities; coordinate transformations; forward kinematics of open-chain manipulators; solution of inverse kinematics; robot workspaces; nonlinear decoupling control and force control.
• ELEC 5650

  Introduction to Networked Sensing, Estimation and Control

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910E

  Background

  ELEC 2600 AND ELEC 3200

  Description

  The course gives an introduction to the analysis and design of sensing, estimation and control systems in a networked setting. It consists of three parts: the first part introduces necessary background knowledge in communication networks, sensor networks, linear state estimation, MAP and ML estimators, Kalman filtering, and modern control theory; the second part focuses on analysis of network effect to remote state estimation and control; the third part presents some advanced topics including distributed state estimation and resource allocation through scheduling.
• ELEC 5660

  Introduction to Aerial Robotics

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910P

  Background

  Linear algebra; Probability; MATLAB programming skills; C++ programming skills

  Description

  This course gives a comprehensive introduction to aerial robots. The goal of this course is to expose students to relevant mathematical foundations and algorithms, and train them to develop real-time software modules for aerial robotic systems. Topics to be covered include rigid-body dynamics, system modeling, control, trajectory planning, sensor fusion, and vision-based state estimation. Students will complete a series of projects which combine into an aerial robot that is capable of vision-based autonomous indoor navigation.
• ELEC 5680

  Advanced Deep Learning Architectures

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910T

  Co-list with

  COMP 5214

  Exclusion(s)

  COMP 5214

  Description

  This course focuses on advanced deep learning architectures and their applications in various areas. Specifically, the topics include various deep neural network architectures with applications in computer vision, signal processing, graph analysis, and natural language processing. Different state-of-the-art neural network models will be introduced, including graph neural networks, normalizing flows, point cloud models, sparse convolutions,and neural architecture search. The students have the opportunities to implement deep learning models for some AI-related tasks such as visual perception, image processing and generation, graph processing, speech enhancement, sentiment classification, and novel view synthesis.
• ELEC 5690

  Advanced Topics in Artificial Intelligence for Medical Image Analysis

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910X

  Background

  Students should have a bachelor's degree in an engineering-related discipline

  Description

  This course provides an introduction to the latest advancements in the broad area of artificial intelligence and its applications in healthcare. It covers basic concepts of deep learning as well as advanced approaches for analyzing diverse healthcare data, including medical images, clinical reports, and biological data. Through hands-on homework projects, students are expected to demonstrate their capability in applying fundamental deep learning techniques to tackle various real-world healthcare problems and challenges.
• ELEC 5810

  Introduction to Bioinformatics Algorithms

  [3 Credit(s)]
  Mode of Delivery

  [BLD] Blended learning

  Description

  This is an introductory course on computational biology at the molecular level. It will cover basic biological knowledge, important biological questions, common data acquisition techniques, popular data analysis algorithms and their applications. The major content of this course is computation-oriented.
• ELEC 5820

  Microfluidics and Biosensors

  [3 Credit(s)]
  Previous Course Code(s)

  ELEC 6910D

  Co-list with

  BIEN 5820

  Exclusion(s)

  BIEN 5820

  Background

  Basic Physics

  Description

  Introduction to Microfluidics and Biosensors; Overview of microfabrication materials & techniques; microfluidic principles; miniaturized biosensors; micro total analysis system (µTAS) & lab-on-a-chip (LOC) for clinical and research applications.
• ELEC 5900

  Modern Engineering Research Methodologies

  [3 Credit(s)]
  Exclusion(s)

  EESM 5770 (prior to 2025-26), EESM 5830

  Description

  The course provides a high-level description of modern engineering research practices. It covers topics including research mentality, the scientific method, evaluating research topics, literature search, report writing, presenting data, publication, research management, research ethics and technology transfer.

  Intended Learning Outcomes

  On successful completion of the course, students will be able to:

  • 1.
    Summarise scientific methodologies used in modern engineering research practices.
  • 2.
    Distinguish and categorize different types of research.
  • 3.
    Evaluate the quality of research papers.
  • 4.
    Develop a research proposal independently.
  • 5.
    Evaluate and write a critical review of a research paper.
  • 6.
    Identify different components in a published paper.
• ELEC 6900

  Independent Study

  [1-3 Credit(s)]
  Description

  Selected topics in electronic and computer engineering studied under the supervision of a faculty member. Graded P or F.
• ELEC 6910-6940

  Special Topics

  [1-4 Credit(s)]
  Description

  Selected topics of current interest. May be repeated for credit, if different topics are covered.
• ELEC 6950

  Departmental Seminar

  [0 Credit(s)]
  Description

  Series of seminar topics presented by students, faculty and guest speakers. Graded P or F.
• ELEC 6990

  MPhil Thesis Research

  [0 Credit(s)]
  Description

  Master's thesis research supervised by a faculty member. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.
• ELEC 7990

  Doctoral Thesis Research

  [0 Credit(s)]
  Description

  Original and independent doctoral thesis research. A successful defense of the thesis leads to the grade Pass. No course credit is assigned.