May 2025 Entry
What's New
- Undergraduate
- Taught Postgraduate
- Undergraduate
The Department currently has three main existing research groups, namely, Applied Optimisation and Operations Research, Applied Statistics and Financial Mathematics, and Engineering and Computational Mathematics. Meanwhile, the Department is rapidly developing two new groups, namely, Data Science and Machine Learning, and Mathematical Science, in particular Partial Differential Equations.
The Department offers both MPhil and PhD research programmes in the following five major areas:
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Applied Optimisation and Optimal Control
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Applied Statistics
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Data Science
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Engineering and Computational Mathematics
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Financial Mathematics
World-leading research and top in world rankings
Our research in Mathematics and Statistics has received remarkable recognition since 2009. In the Quacquarelli Symonds (QS) World University Rankings by Subject 2023, PolyU is listed the world top 100 in Statistics and Operational Research and 200 in Mathematics.
AMA’s ranking by different ranking agencies in the past 6 years:
Ranking Agencies | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
Best Global Universities for Mathematics | 52 | 74 | 82 | 110 | 54 | 47 |
The QS World University Ranking by Subject (Mathematics) | 51-100 | 51-100 | 101-150 | 101-150 | 109 | 151-200 |
The QS World University Ranking by Subject (Statistics and Operational Research) | 51-100 | 51-100 | 51-100 | 51-100 | 51-100 | 51-100 |
Our Department has the following infrastructures to promote research collaborations:
CAS AMSS-POLYU Joint Laboratory of Applied Mathematics
Chinese Academy of Sciences (CAS) Academy of Mathematics and Systems Science (AMSS) and the Hong Kong Polytechnic University (PolyU) Joint Laboratory of Applied Mathematics is one of the 22 CAS joint laboratories with universities of Hong Kong, which were approved by CAS in October 2018. The CAS AMSS-PolyU Laboratory has three research groups with members from AMSS and PolyU, and will capitalise on their specialities to extend the frontiers of research in applied mathematics. For more details, please visit https://www.polyu.edu.hk/ama/research-and-consultancy/cas-amss-polyu-jlab/
The PolyU-SDU Joint Research Center on Financial Mathematics
The PolyU-SDU Joint Research Center on Financial Mathematics was established in 2010 to promote research collaboration on Financial Mathematics among researchers of The Hong Kong Polytechnic University (PolyU) and Shandong University (SDU). It fosters technical exchange and research cooperation between Mainland China and Hong Kong, and allows the Party to capitalise on their specialities to extend the frontiers of Financial Mathematics.
Statistical Advisory Unit
The Department has a Statistical Advisory Unit that provides both internal and external statistical consultancy and advisory services.
The University Research Facility in Big Data Analytics (UBDA)
The University Research Facility in Big Data Analytics (UBDA) was established on 8 May 2018. It is the first university-wide research facility in big data analytics among the universities in Hong Kong. The facility is jointly managed by big data experts from the Department of Computing and AMA and representatives from other disciplines. UBDA will provide consultancy service and technical support to PolyU research community and industry partners, assisting them in developing innovative solutions to research problems and application challenges by capitalising on the use of models, algorithms and platforms for big data analytics and processing. Our Department will facilitate multidisciplinary research in big data.
Research Centre for Quantitative Finance
The Research Centre for Quantitative Finance aims to promote research, education, and academia-industry collaborations in the field of quantitative finance. The centre will bring together experts from relevant fields such as finance, mathematics, statistics, and data science at The Hong Kong Polytechnic University.
Applied Optimisation and Optimal Control
- Computational optimal control
- Financial engineering
- Mathematical programming
- Nonlinear optimisation
- Signal processing
- Statistical Optimization
- Optimization Software
Applied Statistics
Biostatistics
High-dimensional data analysis
Network analysis
Statistical learning
Survival analysis
Time series analysis
Data Science
- Data Science and Machine Learning
Operations Research
Forecasting
Heuristics
Inventory control
Manufacturing network flows
Supply chain management
Transportation
Operations Optimization
Engineering and Computational Mathematics
Mathematical biology and epidemiology
Nonlinear Partial Differential Equations
Numerical linear algebra
Numerical methods for differential equations
Numerical Software
Financial Mathematics
Financial engineering
Investment science
Mathematical finance
FinTech
The Department recognises the ever-increasing demand for computational power in teaching and research. In view of this, the Department has recently deployed nine high-performance servers as follows:
Server | Arch. | Processor | CPU cores | Max. Threads | CPU Clock | RAM | Operating system |
amaws1 | X86_64 | 4 x Intel(R) Xeon(R) E7-4890 v2 | 60 | 120 | 2.8~3.4 GHz | 1536GB | CentOS 8.2 |
amaws2 | X86_64 | 4 x Intel(R) Xeon(R) E7-4890 v2 | 60 | 120 | 2.8~3.4 GHz | 1536GB | CentOS 8.2 |
amaws3 | X86_64 | 2 x Intel(R) Xeon(R) E5-2683 v4 + 2 x Tesla K80 GPU | 32 | 64 | 2.1~3.0 GHz | 512GB | Ubuntu 20.04LTS |
amaws4 | X86_64 | 2 x Intel(R) Xeon(R) E5-2683 v4 | 32 | 64 | 2.1~3.0 GHz | 64GB | Ubuntu 20.04LTS |
amaws5 | X86_64 | 2 x AMD EPYC 7742+ 4 x NVIDIA A100 GPU | 128 | 256 | 2.25~3.4 GHz | 1536GB | Ubuntu 22.04LTS |
amaws6 | X86_64 | 2 x Intel(R) Xeon(R) Gold 5215 | 40 | 80 | 2.5~3.4 GHz | 256GB | Ubuntu 22.04LTS |
amaws7 | X86_64 | 2 x AMD EPYC 7763 | 128 | 256 | 2.5~3.5 GHz | 1024GB | Rocky Linux 9.0 |
amaws8 | X86_64 | 2 x AMD EPYC 7763 | 128 | 256 | 2.5~3.5 GHz | 1024GB | Rocky Linux 9.0 |
amaws9 | X86_64 | 2 x Intel Xeon(R) 6248 Gold + 8 * NVIDIA A40 GPU | 48 | 96 | 3.0~4.0GHz | 768GB | Rocky Linux 9.0 |
Together with a 128-processor computer cluster with parallel computing capability, the Department’s computer facilities can efficiently help staff and students to conduct research on big data analysis and applied mathematics.
The mathematics laboratories are equipped with up-to-date PCs with various software, colour laser printers, projectors and audio-visual facilities to support the teaching of mathematics and statistics. The Department has also installed eight Bloomberg terminals to allow staff and students to obtain updated financial data via the renowned Bloomberg Financial Information System.
Compulsory - Two Academic Referee's Reports are required.
Compulsory
Compulsory
Compulsory - A standard form must be used for the submission of research proposal. Please click here to download the form.
Compulsory