The Hong Kong Polytechnic University

What you'll study

This MSc combines foundations in artificial intelligence and machine learning with specialist applications for architecture, urban design and habitat studies. Core topics typically include computational design workflows, generative design algorithms, supervised and unsupervised machine learning, spatial and temporal data analytics, building information modelling (BIM) integration, environmental and performance simulation, and digital fabrication strategies.

Programme components commonly include taught modules, lab‑based studios and a substantial independent project or dissertation that applies AI methods to an architectural or habitat design problem. Typical module examples are:

• Foundations of Machine Learning for Design — core algorithms and model evaluation tailored to design data.
• Generative and Parametric Design — procedural modelling, optimisation and evolutionary techniques.
• Spatial Data Analytics and GIS for Built Environments — handling urban and sensor datasets.
• Performance Simulation and Environmental Intelligence — energy, daylighting and thermal modelling informed by AI.
• Digital Fabrication and Robotic Construction — translating algorithmic outputs to physical prototypes.
• Ethics, Governance and Human Factors in AI — responsible deployment in the built environment.

Teaching methods emphasise studio practice, hands‑on coding workshops, collaborative multidisciplinary projects and engagement with real‑world datasets. The programme is available with full‑time and part‑time study modes where offered, and culminates in a research‑led design thesis or applied project developed with faculty supervision and, where possible, industry partners.

Entry requirements

Applicants are normally expected to hold a recognised bachelor’s degree in architecture, urban planning, civil or building engineering, design, computer science or a related discipline. Professional experience in architecture, design practice, or a technology role in the built environment is an advantage. A portfolio demonstrating design work, computational projects or relevant technical experience is usually required.

Successful applicants should have basic programming familiarity (for example with Python, scripting in Rhino/Grasshopper or similar) or demonstrate a readiness to acquire these skills. International applicants whose first language is not English must meet the university’s English language proficiency requirements.

Career prospects

Graduates pursue roles that bridge design, technology and analytics across architecture, construction and urban sectors. Typical career paths include:

• Computational designer or digital design lead in architecture and multidisciplinary design firms.
• AI and data analyst roles within urban planning, smart city or infrastructure consultancies.
• Building performance modeller and sustainability consultant using AI‑enhanced workflows.
• R&D or innovation positions in construction technology companies and startups, including digital fabrication and robotics.
• Academic or research assistant posts in universities and research institutes focusing on AI applications for the built environment.

Graduates are well placed to work on projects that require integrating large datasets, automating design exploration, improving environmental performance and developing new construction technologies.

Why study at The Hong Kong Polytechnic University

The Hong Kong Polytechnic University is known for its applied focus and strong industry engagement across design, engineering and built‑environment disciplines. Students benefit from multidisciplinary collaboration across departments, access to advanced digital fabrication and modelling facilities, and opportunities to work on projects with local and regional industry partners.

The university’s location in Hong Kong provides direct exposure to dense urban contexts, high‑rise construction practices and innovation ecosystems in Asia, offering a distinctive laboratory for testing AI applications in architecture and habitat design. The programme emphasises practical, project‑based learning aimed at preparing graduates to translate computational research into built outcomes and industry solutions.