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Contents of this publica�on are subject to review and change. Please refer to www.comp.polyu.edu.hk for the latest informa�on.(August 2020)
PolyU COMP
M a s t e r o f S c i e n c e i n
INFORMATIONTECHNOLOGY資訊科技理學碩士學位課程
ARTIFICIAL INTELLIGENCEBIG DATA ANALYTICSFINANCIAL TECHNOLOGYCYBER SECURITY & CRYPTOCURRENCYCLOUD COMPUTINGNATURAL LANGUAGE PROCESSINGSOFTWARE DEVELOPMENT & MANAGEMENT
Department of ComputingPQ806
Mong Man Wai BuildingThe Hong Kong Polytechnic University
Hung Hom KowloonHong Kong
Stream in AI and Big Data
Stream in AI and FinTech
Promising career advancementWith the strategic planning and investment of the HKSAR Government on the Smart City initiative, Hong Kong will be moving forward with new development in AI, FinTech, Robotics, and life sciences. Besides, data-driven technology development will be considered by the HKSAR Government as one of the top priorities. Hence, our programme with AI, Big Data and FinTech technologies as the core focus, is rightfully aligned with the strategic direction of the HKSAR Government in technology development. With the increasing demand for IT expertise locally and globally, our graduates, who are well equipped with comprehensive and professional IT knowledge, will be developed to be critical thinkers, effective communicators, innovative problem solvers and socially responsible global citizens. They will embark on promising career development in many sectors.
Advanced learning facilities and joint laboratoriesPolyU has established the University Research Facility in Big Data Analytics (UBDA), the first university-wide research facility in big data analytics among universities in Hong Kong. Equipped with big data expertise in PolyU and the most advanced computing infrastructure and tools today, UBDA is expected to foster cross-disciplinary research collaborations in PolyU, establish a strong partnership with industries on big data analytics applications, and promote big data education in Hong Kong.
At COMP, we have established other joint laboratories and have been working closely with industry-leading companies such as IBM, Microsoft, Yonyou, Alibaba and Tencent. These joint laboratories are not only supporting research activities but also teaching and learning as well as knowledge transfer purposes. They also facilitate students to gain practical knowledge and to keep in pace with the industry development.
TAUGHT POSTGRADUATE PROGRAMMEFEATURES Our programme is a science and technology based programme tailored to nurture Mathematics, Information Systems, Engineering, or other Science graduates to become IT professionals and to enrich Computing/ Computer Science graduates with advanced knowledge and skills in the important areas, especially AI, Big Data and FinTech. The programme provides the knowledge, support and guidance to students to continue lifelong learning and development.
According to Elsevier’s Scopus, PolyU was ranked the 8th in the world and the 1st in Hong Kong in field-weighted citation impact of publications on AI research from 2011 to 2015. COMP conducts advanced research contributing to the world’s fast technological growth and is dedicated to offer computing education that is in line with the development of the latest information technology.
ABOUTTHE DEPARTMENT OF COMPUTINGThe Department of Computing (COMP) has a proud history of 45 years. It was established in 1974 as one the pioneers offering computing education in the territory, nurturing professional talents to support the society’s advancement. Today, COMP has gained international recognition in world-class research and high quality education. It is ranked 51st - 100th in the QS World University Rankings by Subject 2020 – Computer Science & Information Systems and ranked 40th in Computer Science in the “2020 Best Global Universities Rankings” by the U.S. News and World Report.
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We also provide other resources for students to undertake projects and dissertations on different topics. Students have the opportunity to access the Virtual Reality and Augmented Reality System in the Virtual Reality and Game Lab as well as the Big Data and Cloud Computing Platform to perform their research studies. Students are also welcome to attend all the research seminars held by the Department to understand the latest state of research in the IT field.
Practical industry workshops and training sessionsOur programme will offer extra learning opportunities to enhance students’ study experience. Programming workshops will be part of the learning and teaching activities designed to help students with no or limited programming experience. We will offer workshops on various topics including AI, Blockchain and Machine Learning to strengthen students’ technical skills and hands-on experiences. Besides, we will also invite renowned speakers to deliver talks, seminars and forums, such as Cyber Security, FinTech application in banking and insurance industry, ePayment services, Initial Coin Offering to help students enrich industrial experience and raise awareness of the latest technologies development.
Wide variety of subjects that cover hot IT topicsGiven the rapid evolution of the IT industry, this programme offers a range of core and elective subjects that are in line with the fast-changing IT market needs as well as students’ demand especially in the three booming areas: Artificial Intelligence, Big Data and FinTech. Students enjoy flexible options in selecting subjects that fit their interests and career goals. COMP frequently reviews the programme curriculum and we have recently introduced some new subjects such as “Machine Learning and Data Analytics”, “Cyber and Internet Security”, “Distributed Ledger Technology, Cryptocurrency and E-Payment”, “Computer Vision and Image Processing”, etc.
Flexible to choose the mode of study and stream(s) This programme offers both full-time and part-time mode of study. Different study patterns including the combination of a dissertation, a project and subjects of equivalent credits are available for students to choose according to their schedule and preference.
To provide more choices for students according to the development of the global IT industry and the demands of the market, stream(s) are introduced in this programme. Based on their career goal and study plan, students enjoy the flexibility to study a MScIT degree with stream(s) or without stream if they fulfil the stream requirements.
• Stream in Artificial Intelligence and Big Data• Stream in Artificial Intelligence and Financial Technology
Excellent platform for peer learning and exchangeOur programme offers a comprehensive curriculum with cutting-edge subjects to cater for students with different career developmental needs. With such an environment of broad student mix, students benefit not only from learning the fundamental theories, core and applied technologies, and industry best practices but also from interaction with their peers in exchanging ideas and sharing experiences. COMP also maintains an extensive network of MSc alumni, students can acquire both advanced expertise and professional networks that help them scale new heights in their careers.
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PROGRAMMESTRUCTUREStudents can select from a range of subjects offered under the programme. In general, each subject takes place once a week in the evening over a 13-week semester. Full-time students normally take 4 subjects in a semester and complete the study in 1.5 years, whereas part-time students usually take 2 subjects in a semester and complete the study in 2.5 years.
Mode of studyThis is a mixed mode programme that students are required to take 9 credits or more in a semester in order to retain full-time status or they will be given a part-time status. Non-local students subject to visa requirements are required to have full-time status (i.e. to take at least 9 credits for each semester).
Award requirementsTo fulfil the graduation requirement, students can choose to study a MScIT degree with stream(s)# or without stream by taking the required subjects.
Programme Core subjects: P-coreStream Core subjects: S-core
AwardsMScIT with Stream in
Artificial Intelligence and Big Data
MScIT with Stream in Artificial Intelligence and
Financial TechnologyMScIT
With Dissertation3 P-Core +4 S-Core +
1 Dissertation
3 P-Core +4 Electives* +1 Dissertation
With Project
3 P-Core +4 S-Core +
1 Elective* +1 Project
3 P-Core +5 Electives* +
1 Project
Without Dissertation/ Project
3 P-Core +4 S-Core +
3 Electives*
3 P-Core +7 Electives*
Credit Requirement 30 30
*Students can take master level elective subjects within the MScIT programme to satisfy their elective requirements, subject to the pre-requisite and exclusion requirements.
#The streams will not form a part of the official award parchment. A separate certificate will be issued upon completion of stream.
For more information about the curriculum, please visit www.comp.polyu.edu.hk/en-us/prospective-students/taught-postgraduate-programmes.
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List of subjectsWhile every stream has its own group of core subjects, a range of electives is offered depending on the availability of teaching resources and the number of registered students. Students are allowed to choose from a common pool of electives within the Department of Computing, subject to vacancies available.
All subjects below bear three credits unless otherwise stated and they are subject to review and changes.
Programme core subjects: P-coreStream core subjects: S-coreElective subjects: E
MScIT Subject
MScIT with Stream in Artificial
Intelligence and Big Data
MScIT with Stream in Artificial
Intelligence and Financial Technology
MScIT
1 Data Structures and Database Systems P-Core P-Core P-Core
2 Software Engineering and Development P-Core P-Core P-Core
3 Internet Infrastructure and Protocols P-Core P-Core P-Core
4 Artificial Intelligence Concepts S-Core S-Core E
5 Big Data Computing S-Core E E
6 Machine Learning and Data Analytics S-Core E E
7 Computer Vision and Image Processing S-Core E E
8 Financial Computing E S-Core E
9 Cyber and Internet Security E S-Core E
10 Distributed Ledger Technology, Cryptocurrency and E-Payment E S-Core E
11 Advanced Data Analytics E E E
12 Optimization and Applications E E E
13 Natural Language Processing E E E
14 Human Computer Interaction E E E
15 Wireless Networking and Mobile Computing E E E
16 Software Project Management E E E
17 Internet Computing and Applications E E E
18 Multimedia Computing, Systems and Applications E E E
19 Independent Study E E E
20 Project (6 credits) E E E
21 Dissertation (9 credits) E E E
22 Principles of Corporate Finance^ E* E E*
23 Investments^ E* E E*
24 Applications of Computing and Technology in Accounting and Finance I^ E* E E*
25 Business Analytics in Accounting and Finance^ E* E E*
^These subjects are offered by School of Accounting and Finance of PolyU.E*: Not recommended
Credit transferStudents may be given credits for recognised previous study at postgraduate level. The consideration for credit transfer is subject to the maximum validity period of 8 years and the grade performance at B or above. Students should submit an application of credit transfer within the first semester after admission, and it is subject to approval by the Programme Leader.
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OUR STRONG TEAMFaculty Members Research Interests
Prof. BACIU GeorgePhD(Waterloo); MACM; MIEEE
Computer Graphics, Virtual Reality, Data Visualization, Collision Detection, Motion Synthesis and Dynamics of Large-Scale Deformable Surfaces, Virtual Clothing, Geometric Modeling, Texture Analysis, Image Processing
Prof. CAO JiannongPhD(Washington State); FIEEE; DMACM; SMCCF
Parallel and Distributed Computing, Wireless Networks and Mobile Computing, Big Data and Cloud Computing, Pervasive Computing, Fault Tolerant Computing
Dr CAO YixinPhD(TAMU); MACM; MCCF; MSIAM Algorithmic Graph Theory, Combinatorial Optimization, Social Networks, Bioinformatics
Dr CHAN Chun Bun HenryPhD(British Columbia); MIEEE Networking and Communications, Cloud Computing, Internet Technologies, Electronic Commerce
Dr CHUNG Fu Lai KorrisPhD(CUHK); MIEEE Data Mining, Machine Learning, Big Data Analytics, Computational Intelligence, Pattern Recognition, Multimedia
Dr GAO Shang JasonPhD[PolyU(H.K.)] Information Security, Network Security, Data Privacy, Applied Cryptography, Blockchain System
Dr GUAN NanPhD(Uppsala); MIEEE Real-Time Embedded Systems, Cyber-Physical Systems
Prof. GUO SongPhD(uOttawa); FIEEE Big Data, Edge AI, Mobile Computing, Blockchain, Distributed System
Prof. HOORN JohanPhD(D. Litt.); PhD(D. Sc.) (Vrije University Amsterdam) Social Robotics, Affective Computing, Artificial Creativity, Fundamentals of Data Analysis
Dr HUANG XiaoPhD(TAMU) Data Mining, Network Analysis, Social Media Mining, Knowledge Graph Analytics, Automated/Interactive Machine Learning
Dr JANSSON JesperPhD(Lund) Graph Algorithms, Data Structures and Bioinformatics
Dr LEONG Hong-vaPhD(California); MACM; MIEEE Parallel and Distributed Computing, Distributed Databases, Mobile Computing, Internet Computing
Dr LI Jing AmeliaPhD(CUHK) Natural Language Processing, Social Computing, Machine Learning
Dr LI PingPhD(CUHK) Computer Graphics, Computer Vision, Creative Media, Machine Learning
Prof. LI QingPhD(USC); FIET/IEE; DMCCF; SMIEEE
Multi-modal Data Management, Big Data Analytics and Mining, Machine Learning, Social Media and Web Services, e-Learning Technologies
Dr LI Wenjie MaggiePhD(CUHK); MACM Natural Language Processing, Social Media Mining, Text Mining, Information Retrieval, Extraction and Summarization
Dr LIU Yan FionaPhD(Columbia) Machine Learning, Multimedia Understanding
Dr LOU WeiPhD(Florida Atlantic); MIEEE Mobile Ad Hoc and Sensor Networks, Computer Networks, Mobile Computing, Multimedia Systems
Dr LUK Wing Pong RobertPhD(Southampton); FBCS; SMACM; SMIEEE, CEng, CITP Information Retrieval, Pattern Recognition, Natural Language Processing, Data Structures and Algorithms
Dr LUO Xiapu DanielPhD[PolyU(H.K.)]; MIEEE
Mobile Security and Privacy, Network Security and Privacy, Software Engineering, Blockchain/ Smart Contracts, Internet Measurement, Cloud Computing
Dr NGAI GracePhD(Johns Hopkins) Human Computer Interaction, Human Centered Computing, Natural Language Processing
Prof. PATHAK Ajay KumarPhD(HKU); FIAPR; FIEEE Biometrics, Computer Vision-Based Industrial Inspection
Dr PEI Yu MaxPhD(Nanjing); PhD(ETH Zurich) Automated Program Repair, Automated Software Testing, Mining Software Repositories, Object-Oriented Techniques
Dr SHEN JiaxingPhD[PolyU(H.K.)] Data Mining, Social Computing, Affective Computing, Internet of Everything
Dr SHI JiemingPhD(HKU) Big Data Analytics, Database Management, Machine Learning, Parallel Computing
Dr WANG DanPhD(Simon Fraser) Internet Architecture and Protocols, Computer Networking, Smart City, Big Data
Dr WANG QixinPhD(UIUC) Real-Time/ Embedded Systems, Cyber-Physical Systems
Dr WU XiaomingPhD(Columbia) Machine Learning, Artificial Intelligence, Pattern Recognition, Data Mining, Computer Vision, Natural Language Understanding
Dr XIAO BinPhD(UT Dallas); SMIEEE; MACM; MCCF Artificial Intelligence and Network Security, Data Privacy, Blockchain Systems
Dr XU LinchuanPhD[PolyU(H.K.)] Data Mining, Deep Learning, Biomedical Informatics
Dr XUE LeiPhD[PolyU(H.K.)] Mobile System Security, Network System Security, Telematics Security, Network Measurement
Dr YANG LeiPhD(Xi’an Jiaotong) RFID System, Pervasive and Wireless Computing, Internet of Things, Smart Home
Dr YIU Man Lung KenPhD(HKU) Data Engineering, Query Processing, Spatial Database Systems
Prof. YOU Jia JanePhD(La Trobe); Dip(Beijing Foreign Language); MIEEE Image Processing, Pattern Recognition, Computer-Aided Diagnosis and Monitoring
Prof. ZHANG LeiPhD(Northwestern Polytechnical); FIEEE Computer Vision, Pattern Recognition, Deep Learning, Image and Video Processing
Dr ZHENG YuanqingPhD(NTU); MIEEE, MACM Human Centered Computing, Mobile and Network Computing, Wireless Networks, RFID Systems
Dr ZHOU KaiPhD(Michigan State) AI Security, Data Security and Privacy, Applied Cryptography, Adversarial Network Analysis
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ADMISSIONREQUIREMENTS
• Applicants should possess a Bachelor’s degree in Computing / Computer Science, Mathematics, Information Systems, Engineering, or other Science disciplines. Applicants with a Bachelor’s degree in other disciplines with at least five years significant IT relevant work experience will also be considered.
• If you are not a native speaker of English, and your Bachelor’s degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the following minimum English language requirement for admission purpose:
ᡩ A Test of English as a Foreign Language (TOEFL) score of 80 for the Internet-based test or 550 for the paper-based test; OR
ᡩ An overall Band Score of at least 6 in the International English Language Testing System (IELTS).
More information can be found at www.polyu.edu.hk/study.
Application proceduresTo apply for the programme, applicants can submit their application via an online admission system at www.polyu.edu.hk/admission starting from late September. This programme has a quota for admission therefore early application is strongly encouraged.
Programme code: 61030
Tuition feeLocal students: HK$4,000 per creditNon-local students: HK$4,800 per credit
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Contents of this publica�on are subject to review and change. Please refer to www.comp.polyu.edu.hk for the latest informa�on.(August 2020)
PolyU COMP
M a s t e r o f S c i e n c e i n
INFORMATIONTECHNOLOGY資訊科技理學碩士學位課程
ARTIFICIAL INTELLIGENCEBIG DATA ANALYTICSFINANCIAL TECHNOLOGYCYBER SECURITY & CRYPTOCURRENCYCLOUD COMPUTINGNATURAL LANGUAGE PROCESSINGSOFTWARE DEVELOPMENT & MANAGEMENT
Department of ComputingPQ806
Mong Man Wai BuildingThe Hong Kong Polytechnic University
Hung Hom KowloonHong Kong
Stream in AI and Big Data
Stream in AI and FinTech
