Sept 2027 Entry
1.5 years (Full-time)
2.5 years (Part-time)
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Note to Applicants
The programme has a limited quota for admission. Early application is strongly encouraged.
Early Round: 2026-10-20
Main Round: 2027-02-25
Early Round: 2026-10-20
Main Round: 2027-02-25
What's New
- Undergraduate
- Taught Postgraduate
- Undergraduate
Programme Aims
The Master of Science in Materials Intelligence (MSc in MI) programme aims to achieve the following:
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To provide students with a comprehensive interdisciplinary foundation in Materials Intelligence, covering AI for Science and AI + Materials research, as well as applications of Embodied AI and Physical AI.
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To equip students to use AI, robotics, large language models, digital twins and AI agents to accelerate the design, discovery, synthesis and manufacturing of new materials.
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To enable students to understand and develop advanced materials for AI and robotics industries, including next-generation robotic infrastructure, AI chips, renewable energies and emerging space manufacturing.
Characteristics
The MSc in Materials Intelligence offers interdisciplinary training across advanced materials, artificial intelligence, and robotics, with exposure to AI for Science, Embodied AI, and Physical AI. Students will learn through research-informed teaching, practical projects and engagement with leading universities, research institutions and listed companies. Planned collaborations with leading universities and research institutions, such as the University of Oxford and Suzhou National Laboratory, will provide opportunities for guest lectures and research exposure. Students may also access internship opportunities in Suzhou and Wenzhou. Such experiences can help students connect academic knowledge with research, industrial applications and innovation, supporting future careers in AI, digital twins, robotics and new materials.
Upon successful completion of the required coursework for the respective awards, students will graduate with a Master of Science (MSc) degree in Materials Intelligence. Graduates of this programme will have in-depth knowledge, skills, and experience needed to succeed in the rapidly evolving field of materials intelligence. They will contribute to the development of both AI- and robotics-enabled materials research and the materials foundation required for future AI and robotics systems.
Programme Structure
Students who enrol in the MSc in MI programme gain knowledge across a wide spectrum in the field of materials intelligence. In general, each subject is taught through one evening class per week over a 13-week semester. Full-time students normally take three to five subjects per semester. Part-time students normally take two subjects per semester. Each taught subject is worth three credits, and the dissertation is worth nine credits.
Students must complete:
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7 taught subjects, including at least 4 Core Subjects and 3 Elective Subjects, and a Dissertation; or
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10 taught subjects, including at least 4 Core Subjects and 6 Elective Subjects.
Note:
Students are required to complete the Academic Integrity and Ethics (AIE) Requirement (a 1-credit subject pitched at level 5, normally within their first semester of study) as a graduation requirement. No credit fee is required for this subject.
Core Areas of Study
The programme focuses on the interdisciplinary field of Materials Intelligence through two complementary directions:
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AI and Robotics for Materials, where artificial intelligence and robotic platforms are used to accelerate materials discovery, characterisation, and manufacturing; and
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Materials for AI and Robotics, where functional and advanced materials provide the foundation for next-generation AI systems, intelligent devices, sensing platforms, and robotics.
Information on the subjects offered can be obtained at https://www.polyu.edu.hk/eee/study/information-for-current-students/subject-syllabi/
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Prof. ZHAO Haitao
PhD, MSc, BEng
(This programme is offered subject to approval)
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A Bachelor's degree in Electrical Engineering, Electronics Engineering, Automation Engineering, Transportation Engineering, Materials Science, Physics, Chemistry, Computer Science, Engineering Science, or a related discipline.
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Applicants with a Bachelor's degree in other disciplines who have at least three years of significant working experience in either (1) materials science, (2) machine learning, or (3) robotics 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 University’s minimum English language requirement for admission purposes. Please refer to the "Admission Requirements" section for details.
Individual cases will be considered on their own merits. Applicants may be required to attend interviews or take tests to further demonstrate their language proficiency.
For further information on academic matters, please contact:
Prof. ZHAO Haitao
Tel: (852) 2766 6245
Email: hai-tao.zhao@polyu.edu.hk
For further information on application and admission matters related to the programme, please contact:
EEE General Office
Tel: (852) 2766 6221
Email: eee.tpg@polyu.edu.hk
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Suitable candidates may be invited to attend face-to-face/telephone/online interviews.
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Classes are normally held on weekday evenings.
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The Department reserves the right not to offer any one of the subjects. The offer of subjects is subject to review and change if deemed appropriate by the Department.
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