Postgraduate Programme

The Department of Mechanical and Automation Engineering currently offers research-oriented graduate programme leading to the award of the Master (M.Phil.) or Doctoral (Ph.D.) degrees. Applications from both Hong Kong and overseas will be considered. Financial supports are available to successful applicants.

The department may review earlier those applicants who make their applications before December 1, and may give an early interview in addition to the interview(s) held in February of every year. However, the department might have to wait until the application deadline for the academic year is over before sending out the official admission letters.

MPhil and PhD are registered as two separate streams in the MPhil-PhD programme. A student will be admitted as either an MPhil or PhD student.

Fields of Specialization

Department offers research studies in the following fields:


PhD Stream

The Ph.D. stream has a normative study period of 36 months for full-time students with a research-oriented Master's degree and 48 months for students without one. The maximum period for full-time student with Master’s degree is 72 and 84 months for students without.

All students in the PhD stream will be admitted initially in the “pre-candidacy” status. Upon satisfying the Division’s candidacy requirements, the student will be allowed to progress to the “post-candidacy” status. As a requirement for graduation, students must carry out a substantial amount of research which will lead to original results worthy of publication in scholarly journals.

The Division will consider admission of part-time Ph.D. students with Master's degrees and strong academic records. Part-time students will be required to take regular graduate courses offered in the day time. The normative study period for part-time students with a research master's degree is 48 months and for students without a research master's degree are 64 months. The maximum period is 84 and 100 months respectively.


Students are required to complete at least 4 postgraduate courses (12 units) with at least one ENGG5xxx graduate course with grade B from the Faculty core course list as approved by the Division; register for the relevant thesis research course every term throughout his/her studies; pass the candidacy examination, submit a thesis proposal and pass an oral examination of the thesis proposal.


Students can take courses from the Faculty core course list or from divisions to satisfy the remaining course requirement. A total of 21 units are required for graduation, each with a minimum of B- . Each PhD student has to register for the relevant thesis research course every term throughout his/her studies; submit a thesis proposal and pass an oral examination of the thesis for graduation.


MPhil Stream

The M.Phil. Stream has a normative study period of 24 months, and a maximum period of 48 months. Students are required to complete at least 4 graduate courses with a total of 12 units (each with a minimum of B-), as approved by the Division and register for the relevant thesis research course every term throughout their studies until the thesis is finally submitted. In addition, a research project is required for which a thesis is to be submitted with pass an oral defense for graduation.


Qualifications for Admission

The Division of Mechanical and Automation Engineering offer full-time Articulated MPhil-PhD Programme in Mechanical and Automation Engineering. This programme consists of two streams: MPhil stream and PhD stream. Applicant must have majored in a discipline that is related to his/her intended field of MPhil or PhD study, and required to submit a list of research publication, if any. All full-time postgraduate students will receive financial support during their normative study period.

Ph.D. Stream

The applicant shall have:

MPhil Stream

The applicant shall have:

English Language Proficiency Requirements of MPhil-PhD Program:

The applicant should either:



Application Procedures

Applicants may browse detailed information and submit applications through the Graduate School's website (

Office Hours of the Graduate School

Mon-Thu 8:45am to 1:00pm & 2:00pm to 5:30pm
Fri 8:45am to 1:00pm & 2:00pm to 5:45pm
Closed on Saturdays, Sundays and Public Holidays

Supporting documents required include:

1. Completed /Submit Online Application Form (;
2. Official Transcripts from the University attended by applications*;
3. Copies of Degree Certificates;
4. Documents showing the applicant has fulfilled the Graduate School's English Language Proficiency Requirement:
5. Confidential Recommendations from Two referees respectively*;
6. Copies of Identity card or Passport; and
7. Other supporting documents upon request the respective division.
* Official Transcripts and Confidential Recommendation must reach the respective Division directly from the University and referees, or in sealed envelopes and send by the applicant with other support documents to Graduate Division.


Early Admission Scheme

For applicants who (apply for PhD programme directly with CUHK, i.e. non-HKPFS applicants) have completed their applications by 31 December 2016 may receive an early admission decision.



(MPhil-PhD Programme)

Contact person : Ms Joyce Wong
Address : Department of Mechanical and Automation Engineering Room 204, William M.W. Mong Engineering Building,
The Chinese University of Hong Kong,
Shatin, N.T., Hong Kong.
Office hours : Monday-Thursday 8:45am to 1:00pm & 2:00pm to 5:30pm
Friday 8:45am to 1:00pm & 2:00pm to 5:45pm
Closed on Saturdays, Sundays and Public Holidays
Telephone no. : 3943 8345
Fax no. : 2603 6002
Homepage :

(MSc Programme)

Contact person : Miss Winnie WONG
Address : Department of Mechanical and Automation Engineering Room 213, William M.W. Mong Engineering Building,
The Chinese University of Hong Kong,
Shatin, N.T., Hong Kong.
Office hours : Monday-Thursday 8:45am to 1:00pm & 2:00pm to 5:30pm
Friday 8:45am to 1:00pm & 2:00pm to 5:45pm
Closed on Saturdays, Sundays and Public Holidays
Telephone no. : 3943 8337
Fax no. : 2603 6002
Email :
Homepage :


Postgraduate Courses

ENGG 5101 Advanced Computer Architecture

This course is designed to present an overview of some advanced computer architectures and their underlying design principles. Issues discussed will include scalability and performance evaluation. The underlying technologies such as processor and memory hierarchy, cache and shared memory, and advanced pipelining techniques will be presented. Examples of high performance vector processors, multicomputers and massive parallel processors will be compared. Some novel architectures such as VLIW, fault tolerant systems and data flow machines will also be elaborated.

ENGG 5103 Techniques for Data Mining

Data mining provides useful tools for the analysis, understanding and extraction of useful information from huge databases. These techniques are used in business, finance, medicine and engineering. This course will introduce the techniques used in data mining. Topics will include clustering, classifi cation, estimation, forecasting, statistical analysis and visualization tools.

ENGG 5104 Image Processing and Computer Vision

This course will cover fundamental knowledge and advanced topics in image processing and computer vision, including feature detection, segmentation, motion estimation, panorama construction, 3D reconstruction, scene detection and classification, color image processing and restoration. Applications in computer graphics will also be introduced, including image transformation, and camera calibration. Basic concepts of related algorithms and mathematic background will be discussed.

ENGG 5105 Computer and Network Security

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), (v) wireless security (e.g., WiFi security, wireless broadband network security). The course also discusses latest applied security topics depending on the current research trends.

ENGG 5106 Information Retrieval and Search Engines

This course surveys the current research in information retrieval for the Internet and related topics. This course will focus on the theoretical development of information retrieval systems for multimedia contents as well as practical design and implementation issues associated with Internet search engines. Topics include probabilistic retrieval, relevance feedback, indexing of multimedia data, and applications in e-commerce.

ENGG 5108 Big Data Analytics

This course aims at teaching students the state-of-the-art big data analytics, including techniques, software, applications, and perspectives with massive data. The class will cover, but not be limited to, the following topics: advanced techniques in distributed file systems such as Google File System, Hadoop Distributed File System, CloudStore, and map-reduce technology; similarity search techniques for big data such as minhash, locality-sensitive hashing; specialized processing and algorithms for data streams; big data search and query technology; managing advertising and recommendation systems for Web applications. The applications may involve business applications such as online marketing, computational advertising, location-based services, social networks, recommender systems, healthcare services, or other scientific applications.

ENGG 5189 Advanced Topics in Artificial Intelligence

The course introduces fuzzy logic and applications. Fuzzy expert systems. Fuzzy query. Fuzzy data and knowledge engineering. Fuzzy control. Genetic algorithms and programming and their applications. Parallel genetic algorithms. Island model and coevolution. Genetic programming. Introduction to emergent computing.

ENGG 5202 Pattern Recognition

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.

ENGG 5281 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

Review of semiconductor physics. 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. Nanoscale devices: nano- MOSFETs; carbon nanotube devices, nanowire- and nanoparticle-based devices, organic thin film devices, molecular electronic devices, applications, and commercialization.

ENGG 5291 Fiber Optics: Principles and Technologies

Overview of fiber communication technology. Fiber transmission impairments. Introduction to nonlinear optics. Second order and third order nonlinear phenomena. Lightwave propagation in nonlinear media. Optical signal processing in communications. Specialty fibers.

ENGG 5301 Information Theory

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.

ENGG 5302 Random Processes

This course starts with a review of Markov chain, random walk, Poisson process, martingale, and limit theorems. The main content includes a few major topics: Markov process (also called continuoustime Markov chain), renewal theory; queueing theory, and Brownian motion.

ENGG 5303 Advanced Wireless Communications

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.

ENGG 5383 Applied Cryptography

This is a graduate-level course on cryptography. It focuses on the definitions and constructions of various cryptographic schemes and protocols, as well as their applications. Useful tools for securing practical systems and emerging techniques in the applied research community will be introduced. No prior knowledge of security, cryptography, or number theory is required.
- Introduction: a brief history, applications in distributed systems; basic number theory
- Symmetric-key encryption: definition, information-theoretic security, Entropy, PRNG
- Provable security: bounded adversary, random oracle model, basic primitives, reduction
- Public-key encryption: modelling security, Diffie-Hellman protocol, hybrid encryption
- Authentication: Hash function, collision-resistance, MAC, unforgeability
- Public-key infrastructure: certificate management, deployment, and revocation issues
- More schemes: Fiat-Shamir transformation, Cramer-Shoup encryption, identity-/attribute-based encryption, certificateless encryption, proxy re-encryption , broadcast
- Privacy-enhancing cryptography: zero-knowledge proof, anonymous credentials
- Pairing-based cryptography: elliptic curve basic, short signature, searchable encryption

ENGG 5392 Lightwave System Technologies

This course covers the design of advanced optical fiber communication systems. Topics include: optical signal characterization and spectral efficient optical modulation formats, high-speed signal transmission & multiplexing techniques, linear & nonlinear fiber effects and fiber transmission impairments, basic guided-wave optoelectronics and novel integrated optical devices (tunable lasers, planar lightwave circuits, silicon photonics), optical signal amplification, regeneration and performance monitoring techniques, coherent optical communications and enabling digital signal processing techniques, and examples of optical subsystems for optical networks.

ENGG 5402 Advanced Robotics

Lagrange formulation of robot dynamics, Newton-Euler equations; motion control, force control, visual servoing, grasping analysis, object manipulation; sensors and sensor networks, medical robotics, advanced topics in recent development of robotic theory and applications.

ENGG 5403 Linear System Theory & Design

Review on linear algebra; Linear system model and properties; State space representation: equivalent systems, canonical forms, realization, discrete-time systems; Stability: definitions, Lyapunov Theorem; Controllability and Observability: Grammians, canonical decomposition, sampling effects; Minimal realizations; State-Feedback and State-estimators: regulation and tracking, state estimator feedback, reduced-order estimator, multivariable system; Pole placement and Model Matching.

ENGG 5404 Micromachining and Microelectromechanical Systems

Broad overview of microfabrication and microelectromechanical systems. 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. Review of MEMS microsensors, microactuators and microstructures. Topics include accelerometers, pressure sensor, optical switches, cantilever beams, thin-film stress test structures and bulk micromaching test structures. Fundamentals of central dogma of molecular biology, cell and tissue biology. Principles of transduction and measurements of molecules, cells and tissues.

ENGG 5405 Theory of Engineering Design

Introduction of engineering design and design procedure, design innovation and TRIZ, axiomatic design, nature's design and complex systems, design analysis (modeling and simulation), statistical analysis, design optimization, statistical design optimization, Design for Six Sigma (DFSS). Practical examples of design and applications, such as pendulum, bicycle, windmill and propulsion.

ENGG 5501 Foundations of Optimization

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

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

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.

MAEG 5020 Topics in Linear Control Systems(not offer since 2013-14)

Advanced topics in recent development of linear control theory and its applications. The detailed course contents may be changed from year to year depending on the current development.

MAEG 5030 Topics in Computer-Aided Geometric Design

Advanced topics in recent development of computer-aided geometric design. The detailed course contents may be changed from year to year depending on the current development.

MAEG 5060 Computational Intelligence

Concepts, models, methods, and applications of computational intelligence. Topics include neural networks, support vector machines, fuzzy systems, simulated annealing, genetic algorithms, and their applications to control, robotics, automation, manufacturing, and transportation.

MAEG 5070 Nonlinear Control Systems

Ordinary differential equation description of nonlinear state space systems. Phase plane analysis. Linearization. Concepts of stability. Lyapunov theory. LaSalle theory. Limit cycles. Feedback linearization. Sliding mode control. Backstepping.

MAEG 5080 Smart Materials and Structures

Overview of smart materials technology. Characteristics of smart materials such as piezoelectric materials, magnetorheological fluids, and shape memory alloys. Smart actuators and sensors. Structural modelling and design. Dynamics and control for smart structures. Integrated system analysis. Applications in biomedical devices, precision machinery, transportation, and buildings.

MAEG 5090 Topics in Robotics

One or more of the following topics will be discussed in the class. Advanced robot control: adaptive control; cooperative robot control; underactuated robot control; multi-finger hand control. Mobile robot: obstacle avoidance; learning; control; and mobile manipulators. Space robotics: dynamics; control; telescience. Human and robot interaction: interface; learning skills. Biorobotics: robots and intelligent systems for medical, healthcare, and laboratory automation and clinic surgery. Robot motion planning: configuration space; search algorithm; potential field, and sensor-based motion planning.

MAEG 5110 Quantum Control

Mathematics foundation: Hilbert spaces; manifolds; groups; Lie groups and Lie algebras. Physics foundation: quantum phenomena; states and operators; observables and measurement; quantum dynamics. Quantum control systems: modelling; controllability and observability; optimal quantum control.

MAEG 5120 Nanomaterials and Nanotechnology: Fundamentals and Applications

This course provides both fundamental knowledge of nanomaterials and nanotechnology and advanced topics related to applications. These topics cover basic principles, which include the scaling law, the surface science for nanomaterials, observation and characterization tools for nanomaterials, the nanofabrication techniques, building blocks for nanodevices and systems, etc. In the second half of this course, advanced topics on applying nanomaterials and nanotechnology for applications in mechanical engineering, energy engineering and biomedical engineering will be covered.

MAEG 5130 Computational Mechanics

Mechanics is the foundation of many emerging research and engineering topics. With the rapid advancement in computing power, numerical methods are preferred to solve differential equations governing the physical process. It opens a whole new domain in industrial design, manufacturing process analysis, material behaviour prediction, etc. This course covers theoretical fundamentals in computational mechanics, including continuum mechanics, finite element methods, and computational plasticity. In addition, the course will also introduce practical skills to applying computational mechanics in research, including multi-physics simulation and advanced finite element simulation techniques.

MAEG 5140 Materials Characterization Techniques

This course focuses on a suite of materials characterization techniques that are useful in energy and environmental sciences. The main targets of these techniques include functional materials that are used in energy and environmental applications as well as solid, liquid, and gas samples that are involved in energy production and conversion, and pollution monitoring and control. The techniques include mass spectrometry (MS), gas chromatography (GC), high performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR), infrared (IR) spectroscopy, Raman spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), electron microscopy, and X-ray absorption fine structure (XAFS) spectroscopy. Students will receive lectures on the theory and operation principle of each technique as well as its limitations, and obtain hands-on experience with some of the techniques in supplemental lab sessions.

MAEG 5150 Advanced Heat Transfer and Fluid Mechanics

This course will cover advanced topics in heat transfer and fluid mechanics including overview of macroscopic theory of heat transfer, microscopic picture of heat carriers and their transport, micro- and nanoscale energy transport in solids, chemical thermodynamics, chemical kinetics, multicomponent and multiphase mixtures, basic principles of computational fluid dynamics, turbulence modeling, and airflow simulation in enclosed environments.

MAEG 8003/8006/8012 Thesis Research

In this course, a student is required to meet with his/her supervisor regularly who provides necessary guidance and supervision to write up a thesis and monitors the students' academic progress.