Building Machine Learning Surrogate Models with Geometry and Topology

You are cordially invited to attend the lecture by Zheng Hao:

Date and Time: 30 September 2026, 2:00 PM – 3:00 PM

Location: SDE 3, Level 4, LT421

Building Machine Learning Surrogate Models with Geometry and Topology

The seminar will first introduce the key research from the speaker. This research aims at developing a machine learning workflow in solving design-related problems, taking a data-driven structural design method with topological data using graphic statics as an example. It shows the advantages of building machine learning surrogate models for learning the design topology, the relationship of design elements. It reveals a future tendency of the coexistence of the human designer and the machine, in which the machine learns the appearance and correlation between design data, while the human supervises the learning process.

The second part of the seminar will introduce broader applications of machine learning in architectural and urban design, including the machine learning of building and urban morphology.

Dr Zheng Hao is an Assistant Professor and Associate Programme Leader of the Master of Architecture Programme at City University of Hong Kong. He directs the Architectural Intelligence Group and AI Fabrication Lab. His research covers machine learning, AI-generated content, data-driven design, robotic assembly, and bio-inspired 3D printing.

He holds degrees from the University of Pennsylvania, UC Berkeley, and Shanghai Jiao Tong University. Dr Zheng has published approximately 80 papers, led projects exceeding USD 1 million, and received multiple research and teaching awards.