What is in a name?

Our name, StructurAI, reflects our dual focus on structure and AI. ‘Structure’ encompasses our primary interest in the design of building structural systems and extends to our broader fascination with spatial structures across multiple scales in the built environment. It also highlights our pursuit of detecting structures and patterns within these structures, developing effective design insights. While ‘AI’ typically refers to Artificial Intelligence, we equally value the intelligence of architects. We see AI as a tool to augment human capability rather than replace it. We believe that blending both forms of intelligence enables powerful applications.

basic facts

⦿ The lab started on June 2024.
⦿ We are based primarily in University of Hong Kong.
⦿ Our team spans 2 continents, and 3 cities and institutions, consisting of members from 5 countries.

Our core approach

StructurAI develops graph-based machine learning (ML) representations of structural and building systems to help designers better explore equilibrium design solutions and model broader building physics.

Two methods are central: gradients and grammars, which offer complementary ways of embedding engineering knowledge into ML systems and enhancing their ability to reason about design and performance. The former approach, which underpins much of physics-informed ML, is particularly important because it enables AI systems to learn how to solve problems directly, rather than merely memorising patterns from labelled data.

Our applications focus on early-stage design, through tools that directly support form-finding and topology optimisation, as well as broader methods for building analysis and assessment

Where are we?

Room 703 | Department of Architecture | The University of Hong Kong
Knowles Building | Pokfulam Rd | Hong Kong SAR