Description of Postgraduate Courses -- Research Postgraduate Course Sharing Scheme (Fall Term 2019-2020)



Last Update: 2 August 2019 

Please click the prefix of the course you are interested in:


Important Information about HKUST Courses: 

Level of Courses
All courses offered in this scheme are at postgraduate level.

Course Vector and Credits
Each course is assigned a course vector which indicates the number of instructional hours required and credits to be earned.  The course vector is presented in the form of [L-T-Lab:C] where

      L = lecture hours per week
      T = tutorial, seminar or recitation hours per week
      Lab = laboratory or field study hours per week
      C = number of course credits

For example, a course vector of [3-1-2:3] denotes a course that requires 3 lecture hours, 1 tutorial/seminar/recitation hour, and 2 laboratory/field study hours each week, and carries 3 credits.

Medium of Instruction
The medium of instruction is English.  Some courses will have the following notations in the course description to specify the language of reading materials or permitted spoken language (dialect) used in teaching.  


Courses may required students to read materials in Chinese.  Students who have difficulty reading materials in Chinese should consult the instructor concerned prior to enrolling in these courses.

[Pu] / [Ca]

Courses approved to be taught in Chinese carry a [Pu] or [Ca] notation in the course description, which indicates the spoken language used in teaching: [Pu] stands for Putonghua; and [Ca] for Cantonese.



Postgraduate Grades 
Students receive a grade in each course in which they are enrolled.  Grades range in equal increments from A+ to F (i.e. A+, A, A-, B+, B, B-, C+, C or F).   The Pass, Ungraded (P) grade is given only for courses that are indicated in the course description that they will be graded as such. 



BIEN 5050 Global Health Ethics 2-1-0:3
[Previous Course Code(s): BIEN 6930A] Through real-time videoconferencing with participants from different countries such as the United States, United Kingdom, Australia, Mexico, and Philippines, this ONLINE course aims at helping students learn the definitions of global health ethics and bioethics, the different protocol and systems in place to ensure adherence to ethical principles, and how different stakeholders and cultures may interpret ethics differently. Through case studies on ethical challenges from real-world situations, students will analyze and discuss the complexities of global health practice and research ethics in a global context. This course is co-offered with the University of Southern California. Besides the joint LIVE sessions, face-to-face sessions and group projects are also arranged for the introduction of background knowledge, case studies, group project discussion, and technical support.
CHEM 5110 Advanced Organic Chemistry I 3-0-0:3
Mechanism and theory in organic chemistry, molecular orbital theory, structure-activity relationships, isotope effects, solvent effects, neighboring group participation, and reactive intermediates. Background: CHEM 2118 (prior to 2017-18), CHEM 3120 and CHEM 4140
CHEM 5220 Statistical Mechanics: Theory and Applications in Complex Systems 3-0-0:3
Classical statistical mechanics and its applications in complex chemical and biological systems. Background: CHEM 2418 Physical Chemistry (prior to 2018-19)
CHEM 5310 Advanced Inorganic Chemistry I 3-0-0:3
Symmetry, group theory; molecular orbitals, electronic states; ligand field theory; electronic structure of metal complexes; theory of bonding and structure of inorganic compounds; chemistry of the elements; major physical methods used in the determination of molecular structure and bonding.
CHEM 5540 Chemistry for Advanced Materials 3-0-0:3
[Co-list with NANO 5100] Chemistry of materials with nano-dimensional structures and advanced functionalities. Working principles of liquid-crystalline displays and organic light-emitting diodes. High-tech applications of luminescent materials in optoelectronic systems, chemical sensors and biological probes.
Exclusion(s): CHEM 4220, NANO 5100
CIVL 5220 Construction Information Technology 3-0-0:3
[Previous Course Code(s): CIVL 6100B] This course covers the principles and applications of information technology for construction management. Topics include building information modeling, database management and implementation, web-based communication and project management technologies, decision support systems, knowledge management, and data processing and analysis. Background: CIVL 3210
CIVL 5350 Bridge Engineering 3-0-0:3
This course introduces the limit states design method for bridges, discusses the design philosophy and code requirements and presents examples of analysis and design of bridge super-structure components (using the limit states design method).
CIVL 5410 Physical-Chemical Water/Wastewater Treatment 3-0-0:3
Principles of treatment for removing contaminants from drinking water and municipal wastewaters; includes equalization, neutralization, precipitation, coagulation and flocculation, sedimentation, filtration, air stripping, carbon adsorption, disinfection.
Exclusion(s): CIEM 5460, JEVE 5460
Prerequisite(s): CIVL 3420
CIVL 5460 Landfill Engineering and Design 3-0-0:3
Practical aspects of solid waste collection methods and equipment, current available disposal techniques with emphasis on complete engineering design of landfill systems, and landfill leachate treatment will be included.
Prerequisite(s): CIVL 2410
CIVL 5520 Water Resources Systems Analysis 3-0-0:3
Systems approach to the area of water resources management; includes water resources systems within the context of public investment systems, criteria and design of water management schemes. Background: ECON 2113
CIVL 5610 Urban Transportation Networks Analysis 3-0-0:3
Reviews transportation planning models and traffic analysis; examines the assignment of traffic flow on a network according to user-equilibrium and system optimal objectives; addresses formulation methods and solution techniques. Background: CIVL 3610 AND IEDA 3010
CIVL 5630 Traffic Control Fundamentals 3-0-0:3
Traffic flow fundamentals; microscopic and macroscopic traffic flow characteristics; principle and theory of traffic signals; essential modeling techniques; various traffic signal control models. Background: CIVL 3610
Exclusion(s): CIEM 5630
CIVL 5710 Advanced Soil Mechanics 3-0-0:3
Selected topics from recent advances in theoretical and experimental development in soil mechanics; includes stress-strain behavior of soil, consolidation settlement, drained and undrained strength slope stability problems. Background: CIVL 3740
CIVL 5750 Geotechnical Earthquake Engineering and Soil Dynamics 3-0-0:3
Earthquakes and characterization of ground motions, seismicity assessment, soil dynamics and site response analysis, soil liquefaction assessment and post-liquefaction analysis, seismic analysis of slopes and embankments, lateral earth pressures and retaining systems, dynamic soil-structure interaction. Background: CIVL 3740
CIVL 5760 Geotechnical Site Characterization 3-0-0:3
Presents state-of-the-art geotechnical site characterization methodologies; includes basic principles of site characterization planning, drilling and sampling, soil and rock description, cone penetration test, standard penetration test, pressuremeter test, dilatometer test, geophysical methods, permeability and ground water monitoring, and fundamentals of geostatistics. Background: CIVL 3720 (prior to 2018-19)
CIVL 5770 Unsaturated Soil Mechanics and Engineering 3-0-0:3
Fundamental principles, stress state variables, steady-state and transient flows, theory of shear strength and its measurements, soil stiffness, plastic and limit equilibrium analyses of earth pressures, slope stability and bearing capacity, critical state framework, instrumentation, engineering applications on slopes including static liquefaction of loose fill slopes, foundations, forensic studies such as slope failures. Background: first degree in Civil Engineering
Exclusion(s): CIEM 5770
Prerequisite(s): CIVL 3740 or equivalent
CIVL 6050S Civil Engineering Seminar I 1-0-0:0
Discussion of current research by faculty members, and guest lectures on recent advances in civil engineering. Graded P or F.
COMP 5211 Advanced Artificial Intelligence 3-0-0:3
This advanced AI course will cover advanced concepts and techniques in AI.  The major topics will be: problem solving, knowledge and reasoning, planning, uncertain knowledge and reasoning, learning, and robotics.
COMP 5222 Statistical Learning Models for Text and Graph Data 3-0-0:3
[Co-list with MATH 5471] [Previous Course Code(s): COMP 6211B] This course will introduce a number of important statistical methods and modeling principles for analyzing large-scale data sets, with a focus on complex data structures such as text and graph data. Topics covered include sequential models, structure prediction models, deep learning attention models, reinforcement learning models etc., as well as open research problems in this area.
Exclusion(s): COMP 4221, COMP 5221, MATH 5471
COMP 5331 Knowledge Discovery in Databases 3-0-0:3
An introduction to knowledge discovery in databases.  Different discovery and learning techniques are presented and compared.  Automatic generation of query language expressions is discussed in depth.  Potential applications are shown. Background: COMP 3311
COMP 5411 Advanced Computer Graphics 3-0-0:3
The first part of this course covers an introduction to mathematical tools and computational techniques for image synthesis and manipulation of 3D models.  The second part covers more advanced topics which may include digital geometry processing, image processing, visualization, GPU computing, numerical optimization methods. Background: COMP 3711, Linear Algebra, Calculus
Exclusion(s): CSIT 5400
COMP 5621 Computer Networks 3-0-0:3
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(s): COMP 4622 (prior to 2018-19)
COMP 5631 Cryptography and Security 3-0-0:3
Classical encryption techniques, block and stream ciphers, public-key cryptography, authentication, nonrepudiation, key management, digital signatures, public key infrastructure, cryptographic protocol, secret sharing, electronic mail security, IP security, Web security, Firewalls, Intrusion detection. Background: Computer networks
Exclusion(s): CSIT 5710
COMP 5711 Introduction to Advanced Algorithmic Techniques 3-0-0:3
This is an introductory graduate course in algorithmic techniques.  Topics include: advanced data structures; graph algorithms; amortization; approximation algorithms; on-line algorithms; randomized and probabilistic analysis. Background: COMP 3711, COMP 3721
COMP 6211D Deep Learning 3-0-0:3
This course focuses on deep learning and its applications in various areas. The topics include the basis of deep learning and its applications in computer vision, speech processing, optimization, reinforcement learning, and natural language processing. Specifically, various forms of deep neural networks will be introduced, such as convolutional neural networks, context aggregation networks, recurrent neural networks, graph neural networks, and generative adversarial networks. The students have the opportunities to implement deep learning models for some AI tasks such as image understanding, image synthesis, graph analysis, and speech enhancement.
ELEC 5010 Introduction to the Design & Implementation of Micro-Systems 3-0-1:3
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.
Exclusion(s): MECH 5950
ELEC 5040 Advanced Analog IC Analysis and Design 3-0-0:3
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. Background: ELEC 4420 and ELEC 4510
Exclusion(s): EESM 5120
ELEC 5050 Advanced CMOS Devices 3-0-0:3
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.
Prerequisite(s): ELEC 3500
ELEC 5070 Microelectronics Fabrication Technology 3-0-0:3
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 5090 Advanced Photonics Technologies 3-0-0:3
A brief review of modern optics theories, Fourier optics based devices and systems, fundamentals of laser physics, optoelectronics, nonlinear optics and laser spectroscopy.
ELEC 5300 Stochastic Processes 3-0-0:3
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. Background: ELEC 2600
ELEC 5360 Principles of Digital Communications 3-0-0:3
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. Background: Probability theory
Exclusion(s): EESM 5536
ELEC 5470 Convex Optimization 3-0-0:3
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. Background: Linear algebra (also basic digital communications and basic signal processing)
ELEC 5540 High Tech Innovation and Entrepreneurship 3-0-0:3
[Previous Course Code(s): ELEC 6910I] This interdisciplinary class combines a technical survey of emerging technologies/innovation with practical high-tech entrepreneurship training. It surveys a few major areas of innovation that will change the future landscape of the high-tech industry, with notable guest lecturers describing business cases and providing an industrial perspective. The class also introduces practical entrepreneurship principles for business development. Students will learn important skills such as building teams and attracting talent, developing a product/technology roadmap, marketing and selling an idea, company structuring, managing rapid growth, venture fund raising, forming strategic partnerships, and developing and intellectual property strategy. Students will form multi-disciplinary teams to write real-world business plans. Each team will develop a business model and execution plan based on its members' interests.
Exclusion(s): CSIT 6000C, EESM 5810 (prior to 2019-20), ELEC 6910N, SBMT 6010K
ELEC 5600 Linear-System Theory 3-0-0:3
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. Background: ELEC 2100, MATH 2350 and MATH 2352
ELEC 6910T Deep Learning 3-0-0:3
This course focuses on deep learning and its applications in various areas. The topics include the basis of deep learning and its applications in computer vision, speech processing, optimization, reinforcement learning, and natural language processing. Specifically, various forms of deep neural networks will be introduced, such as convolutional neural networks, context aggregation networks, recurrent neural networks, graph neural networks, and generative adversarial networks. The students have the opportunities to implement deep learning models for some AI tasks such as image understanding, image synthesis, graph analysis, and speech enhancement.
HUMA 5270 Cantonese Linguistics 3-0-0:3
This course deals with various issues of Cantonese, including sounds and tones, word formation, syntax and pragmatics. It will review the history of the language by studying texts from the early 19th century to the present; and examine the current linguistic changes that have redefined Hong Kong speech as a special variety of Cantonese. [PU][C]
HUMA 5450 Taiwan and Hong Kong Fiction 3-0-0:3
A critical study of development, trends, characteristics of narrative literature in Taiwan and Hong Kong from the late 1960 to the present from cultural, historical, and gender perspectives. [PU][C]
HUMA 5690 Major Issues in the History of U.S.-China Relations 3-0-0:3
This course examines the historical origins and evolution of the complex relations between China and the United States from the early 19th century to the late 20th century. It explores some of the most important events and persistent issues in political, military, economic, and cultural relations between the two countries. It also introduces students to major competing interpretations by American and Chinese scholars. [C]
HUMA 5695 Fascism 3-0-0:3
This course aims to provide students with an introduction to the comparative study of twentieth-century dictatorships. Course readings will focus on Italian Fascism and National Socialism, but the overarching theoretical perspectives will be relevant to students of non-European dictatorships as well.
Exclusion(s): HUMA 602N
HUMA 5770 Field Research: Theory and Practice 3-0-0:3
[Previous Course Code(s): HUMA 5550] Theories, methods, and techniques in ethnographic field research are explored. Students conduct individual and group research projects.
Exclusion(s): MGCS 5031 (prior to 2018-19)
HUMA 5820 Confucianism: Song and Ming Periods 3-0-0:3
A course on the Song and Ming Neo-Confucianism as a revivalist movement. Close reading and exploration of a selected number of texts. [PU][C]
HUMA 6001V Sentimental Republic: Emotion in Modern Chinese Literature 3-0-0:3
This course will employ an interdisciplinary approach to an examination of Chinese literature and culture from the late Qing to the Republican era, with a focus on the expression and representation of emotion and affect. [C]
HUMA 6001X Socialist Film Culture 3-0-0:3
This graduate course will explore the film culture under Mao (1949-1976). Focusing on a variety of cinematic forms and genres, it roughly consists of three parts. The first part examines the beginning and development of socialist cinema during the Seventeen Years (1949-1966). The second part is devoted to the films made during the Cultural Revolution (1966-1976). The third part touches upon the post-Mao films that represent the Cultural Revolution in retrospect. The major theoretical problematic of the course resides in the complicated relationship between totalitarian politics and cinematic aesthetics. It will also explore other related theoretical issues such as national identity, ethnicity, women, children, and animals.
HUMA 6003E Philosophy of History and Society 3-0-0:3
This course will introduce students to key questions in the philosophy of history and society in the context of the development of modern German philosophy from German Idealism and Marxism to Hermeneutics and Critical Social Theory.
LIFS 5710 Cellular Regulation 3-0-0:3
Molecular basis of cellular regulation. Cellular signal transduction cascades.
Exclusion(s): LIFS 6270 (prior to 2014-15)
MARK 5420 Behavioral Decision Theory 3-0-0:3
[Previous Course Code(s): MARK 6900H] This course is designed to familiarize students with a wide variety of issues related to consumer judgment and decision making. In addition to providing students with basic knowledge on behavioral decision theory, this course will provide rigorous training to students to generate their own research ideas that lead to projects that are doable and worth doing. The readings will be from Consumer Behavior/Marketing as well as the basic disciplines of Economics and Psychology.
MATH 5011 Advanced Real Analysis I 3-0-0:3
Basic topology, continuous function spaces, abstract measure and integration theory, Lp spaces, convexity and inequalities, Hilbert spaces, Banach spaces, Complex measure. Background: MATH 3033
MATH 5111 Advanced Algebra I 3-0-0:3
Advanced theory of groups, linear algebra, rings, modules, and fields, including Galois theory. Background: MATH 3121 and MATH 4121 (prior to 2014-15)
MATH 5230 Differential Topology 3-0-0:3
Manifolds, embedding and immersion, Sard's theorem, transversality, degree, vector fields, Euler number, Euler-Poincare theorem, Morse functions. Background: MATH 4225
MATH 5251 Algebraic Geometry I 3-0-0:3
Projective spaces, algebraic curves, divisors, line bundles, algebraic varieties, coherent sheaves, schemes. Some commumative algebra and homological algebra such as notherian ring, regular ring, valuation ring, kahler differentials. Background: MATH 5111 or equivalent postgraduate algebra
MATH 5285 Applied Analysis 3-0-0:3
[Previous Course Code(s): MATH 6050B] Contraction mapping theorem, Fourier series, Fourier transforms, Basics of Hilbert Space theory, Operator theory in Hilbert Spaces, Basics of Banach space theory, Convex analysis. Background: Undergraduate course of multivariable calculus, linear algebra, and real analysis
MATH 5311 Advanced Numerical Methods I 3-0-0:3
Numerical solution of differential equations, finite difference method, finite element methods, spectral methods and boundary integral methods.  Basic theory of convergence, stability and error estimates.
MATH 5350 Computational Fluid Dynamics for Inviscid Flows 3-0-0:3
Derivation of the Navier-Strokes equations; the Euler equations; Lagriangian vs. Eulerian methods of description; nonlinear hyperbolic conservation laws; characteristics and Riemann invariants; classification of discontinuity; weak solutions and entropy condition; Riemann problem; CFL condition; Godunov method; artificial dissipation; TVD methods; and random choice method.
MATH 5351 Mathematical Methods in Science and Engineering I 3-0-0:3
Modeling and analytical solution methods of nonlinear partial differential equations (PDEs). Topics include: derivation of conservation laws and constitutive equations, well-posedness, traveling wave solutions, method of characteristics, shocks and rarefaction solutions, weak solutions to hyperbolic equations, hyperbolic Systems, linear stability analysis, weakly nonlinear approximation, similarity methods, calculus of variations.
MATH 5380 Combinatorics 3-0-0:3
Enumerative Combinatorics: bijective counting, permutation statistics, generating functions, partially ordered sets, Mobius inversions, Polya theory. Graph Theory: cycle space, bond space, spanning-tree formulas, matching theory, chromatic polynomials, network flows. Matroid Theory: matroid axioms, representations, duality, lattice of flats, transversals. Background: Linear algebra; Calculus
Prerequisite(s): MATH 2343 or MATH 3343
MATH 5411 Advanced Probability Theory I 3-0-0:3
Probability spaces and random variables, distribution functions, expectations and moments, independence, convergence concepts, law of large numbers and random series.
MATH 5431 Advanced Mathematical Statistics I 3-0-0:3
Theory of statistical inference in estimation. Topics include: sufficiency, ancillary statistics, completeness, UMVU estimators, information inequality, efficiency, asymptotic maximum likelihood theory. Other topics may include Bayes estimation and conditional inference.
MATH 5471 Statistical Learning Models for Text and Graph Data 3-0-0:3
[Co-list with COMP 5222] [Previous Course Code(s): MATH 6450D] This course will introduce a number of important statistical methods and modeling principles for analyzing large-scale data sets, with a focus on complex data structures such as text and graph data. Topics covered include sequential models, structure prediction models, deep learning attention models, reinforcement learning models, etc., as well as open research problems in this area.
Exclusion(s): COMP 5222
MATH 5520 Interest Rate Models 3-0-0:3
Theory of interest rates, yield curves, short rates, forward rates. Short rate models: Vasicek model and Cox-Ingersoll-Ross models. Term structure models: Hull-White fitting procedure. Heath-Jarrow-Morton pricing framework. LIBOR and swap market models, Brace-Gatarek-Musiela approach. Affine models.
Exclusion(s): MAFS 5040
MATH 6150H Introduction to Cluster Algebra 3-0-0:3
"How do you describe a matrix where the determinant of every submatrix is positive?" The answer to this simple question has a rich algebraic structure. The theory of Cluster Algebra was introduced in 2000 to study the above problem of "total positivity". This new theory quickly becomes one of the most important research areas in mathematics, which finds applications in representation theory, combinatorics, hyperbolic geometry, algebraic geometry, dynamical systems, quantum theory and mathematical physics. This is an introductory course for graduate and advanced undergraduate students. After treating carefully the basics, we will survey some of the research topics in cluster algebra, covering the required backgrounds, if necessary.
Prerequisite(s): MATH 3131 OR MATH 5111
MATH 6380O Deep Learning: Toward Deeper Understanding 3-0-0:3
This course is inspired by Stanford Stats 385, Theories of Deep Learning, taught by Prof. Dave Donoho, Dr. Hatef Monajemi and Mr. Vardan Papyan. The aim of this course is to be provide graduate students who are interested in deep learning a variety of mathematical and theoretical understanding of neural networks which are currently available in research, in addition to some preliminary tutorials. Students with mathematical maturity on approximation theory, optimization, and statistics will be helpful.
MATH 6380R Theoretical Neuroscience 3-0-0:3
Theoretical neuroscience aims to understand the principle mechanisms of brain function using mathematical models. It develops concepts and insights that has been crucial for experimental design and data interpretation. The technical challenges it faces, such as analyzing nonlinear systems with broadly interacted units, are also relatable to other application scenarios of mathematical modeling. We will introduce classic models and results on the main topics of the field, including neural coding of sensory information, dynamics of neural circuits, decision making, memory, and learning. As a rapidly developing field with many open questions, we will also discuss the latest research in these topics. Experience in programming using python, Matlab, etc. is required. No prior knowledge of neurobiology is formally required but is encouraged, and we will introduce the necessary background in the course. Students without prerequisites should seek approval from the instructor to take the course.
Prerequisite(s): MATH 2023 AND MATH 2121 AND MATH 2352 AND MATH 2421
MATH 6450F Advanced Algorithms and Theory of Machine Learning 3-0-0:3
This is an advanced graduate course for students who are already familiar with machine learning. The goal is to explore some of the current active research topics in machine learning, through lectures, paper readings and discussions. The topics covered in the course include modern deep learning models and algorithms, representation learning, small sample learning, generative models, and the mathematical theory of deep learning. Students without prerequisites should seek approval from the instructor to take the course.
Prerequisite(s): MATH 5470
MECH 5010 Foundation of Solid Mechanics 3-0-0:3
Continuum concept for deformation of solids; analysis of stress and strain; constitutive equations; solution of problems relevant to materials processing, fracture mechanics and structural analysis; energy methods and numerical solutions. Background: MECH 3020
Exclusion(s): MESF 5010
MECH 5210 Fluid Dynamics 3-0-0:3
Tensor notation, derivation of Navier-Stokes equations, vorticity transport, viscous flow, flow separation, boundary layer, flow instability, turbulent boundary layer, stratified flow, rotating flow. Background: MECH 2210
Exclusion(s): AESF 5210, MESF 5210
MECH 5925 LED Packaging Technology for Solid-State Lighting 3-0-0:3
[Previous Course Code(s): MECH 6910A] This course introduces the packaging technology of light-emitting diodes (LED) for the applications of solid-state lighting (SSL). Detailed topics include the principles of luminance and chromaticity; designs and structures of LED chips, packages, and modules; material selection and packaging processes; characterization of optical, electrical, and thermal performance; reliability tests and considerations.
MECH 5940 Continuum Mechanics for Crystalline Solids 3-0-0:3
[Previous Course Code(s): MECH 6910Q] This is an interdisciplinary course covering the fundamental laws of the mechanics and physics of crystalline solids, the general description of a periodic structure and their specific characterization methods. The course will start with tensor analysis, and basic calculations of tensor fields. After that, basic kinematics such as deformation gradient, Cauchy-Green tensor will be introduced and defined, followed by the mathematical description of symmetry of crystals. Finally, the course will discuss reciprocal lattices and the X-ray diffraction for structural solving. Background: Solid mechanics related courses. Basic symmetry knowledge. Linear algebra and multivariable calculus
Prerequisite(s): MATH 2011 AND MECH 3020
MECH 5950 Introduction to Microsystems: Technology and Devices 3-0-0:3
Physics of Scaling; energy transduction, sensing and actuation principles; micro-fabrication technology and technology fundamentals; film formation, photolithography and etching; integrated Microsystems and Microsystems packaging.
Exclusion(s): ELEC 5010
MECH 5961 Acoustics and Aeroacoustics 3-0-0:3
[Previous Course Code(s): MECH 6910L] The aims of this module are to acquaint students with the knowledge of acoustics and aerodynamically generated sound, its generation either through turbulent flow or unsteady aerodynamic force-surface interaction, and numerical methods for accurate numerical prediction of aerodynamically generated noise as well as its propagation and far-field characteristics. The wide applications of the subject are noise, environmental impact of noise and transport related noise.
Prerequisite(s): MECH 3640
PHYS 5110 Mathematical Methods in Physics 4-0-0:4
Review of vector analysis; complex variable theory, Cauchy-Rieman conditions, complex Taylor and Laurent series, Cauchy integral formula and residue techniques, conformal mapping; Fourier series; Fourier and Laplace transforms; ordinary differential equations, Bessel functions; partial differential equations, wave and diffusion equations, Laplace, Helmholtz and Poisson's equations, transform techniques, Green's functions; integral equations, Fredholm equations, kernals; Rieman sheets, method of steepest descent; tensors, contravariant and covariant representations; group theory, matrix representations.
PHYS 5210 Electromagnetic Waves, Maxwell Equations, and Relativity 4-0-0:4
Wave solutions of the Maxwell equations, electromagnetic wave propagation, scattering, and diffraction; Fourier optics; dielectric constant of metals and dielectrics and its analytic properties; guided waves; radiation by accelerating charges; special relativity and the transformation of Maxwell equations; radiation by moving charges.
PHYS 5260 Advanced Quantum Mechanics 4-0-0:4
Discussion of various applications of quantum mechanics, such as collision theory, theory of spectra of atoms and molecules, theory of solids, second quantization, emission of radiation, relativistic quantum mechanics.
PHYS 6810F Modern AMO (Atomic Molecular Optical) Physics with Atoms and Photons 3-0-0:3
Introduction to modern atomic physics with ultracold atoms and photons. The basic theoretical tools for atom optics and quantum optics will be introduced. Basic topics include atom-light interactions, cooling and trapping neutral and charged atoms and molecules, degenerate quantum gases, quantum manipulation and detection of atomic states, ultracold collisions and others which provide the foundations for contemporary research in AMO physics. Recent research works will be also covered including many-body states in optical lattices and synthetic topological states in ultracold atoms.
PPOL 5130 Microeconomics and Public Policy 3-0-0:3
The course covers Microeconomic core modules concerning consumer, firm, and market with emphasis on public policy application. A policy topic follows each module enquires students to apply economic model to analyze real world cases and evaluate policies.
SOSC 5440 Economics of Development 3-0-0:3
This course covers the microeconomics of development, focusing on empirical applications. Topics include household models, human resource issues (health and education), intrahousehold economics, rural institutions in land, labor, and credit markets, technology adoption, risk-coping strategies, and evaluation of development projects. Lectures will concentrate on theoretical models and rigorous application of empirical methods, discussing important journal articles. Background: ECON 5110 OR ECON 5130, ECON 5280 OR ECON 5300 OR SOSC 5090
SOSC 5480 Issues in Contemporary Chinese Politics 3-0-0:3
Major political events and basic patterns of political interaction in contemporary China since 1949. Strategic choices of elites and ordinary people. The structural conditions will also be studied in terms of how they would affect political actors' preference and constrain their choices.
Exclusion(s): MGCS 5021, MGCS 5022, SSMA 5060
SOSC 6030L The Belt and Road Initiative: Social Science Perspectives 3-0-0:3
The Belt and Road Initiative (BRI) political and economic mobilization is now a key aspect of China's presence abroad. It mainly involves thousands of investment and infrastructure projects in developing countries, but has many other aspects, including some that are geo-strategic. The US has thus mounted an anti-BRI counter-mobilization that enlists allies, such as India and Japan, to attack the BRI as "Chinese neo-colonialism," a "Chinese debt trap," etc. The global controversy about the BRI has begun to attract social science and other academic analysis. We will use social science theories and concepts, as well as empirical studies, to analyze its dimensions, significance and outcomes. This largely student-led seminar will discuss global and country case analyses of the BRI. Student will also research and write a paper on an aspect of the BRI of his or her choice.
SOSC 6030M Public Ethnography 3-0-0:3
This course introduces students to the theory and practice of participant observation, with a particular focus on using ethnographic research for studying socio-political change in Hong Kong. We begin by reading carefully and critically two examples of ethnography: an urban ethnography in the Chicago School tradition and a comparative ethnography in the extended case method tradition. We will then discuss the methodological and analytical strategies of these two paradigms of ethnographic research. Next, we examine the logic of formulating research questions, sampling, casing, comparison, inter-subjectivity in interviews, concept formation, theoretical construction, ethical and political issues in doing ethnographic fieldwork. For those continuing with the second part of the course in the Spring Semester, we will work together on ethnographic projects related to public sociological issues in Hong Kong. Along with extended immersion in the field, we will learn to code, analyze, conceptualize and theorize from and with the data. The final product of the practicum is a paper that students can submit to professional journals for review and publication.


[C] = Courses may require students to read materials in Chinese. Students who have difficulty reading materials in Chinese should consult the instructor concerned prior to enrolling in these courses.
[Pu] / [Ca] = Courses approved to be taught in Chinese carry a [Pu] or [Ca] notation in the course description, which indicates the spoken language used in teaching: [Pu] stands for Putonghua; and [Ca] for Cantonese.