AI-driven automatic translation of blueprints into construction instructions 

By October 6th, 2025

Project overview

Project title

AI empowers construction: AI-driven automatic translation of blueprints into construction instructions 

Project description

This project develops AI models to address the critical gap in automated interpretation of blueprints in construction domain. The expected outcome is an AI system that translates complex blueprints into plain language actional construction instructions. The project outcome will reduce errors, delays and cost in construction industry, enhancing productivity, safety, and sustainability. 

Supervisory team

University

Name of university supervisorShoujin Wang
Name of universityUniversity of Technology Sydney
Email addressshoujin.wang@uts.edu.au
FacultyEngineering and IT

CSIRO

Name of CSIRO supervisorPiotr Koniusz
Wei Shao
Email addresspiotr.koniusz@data61.csiro.au
wei.shao@data61.csiro.au
CSIRO Research UnitData61

Industry

Name of industry supervisorZiqi Zhou
Name of business/organisationPickc Pty Ltd
Email addresszicci@pickc.ai

Further details

Primary location of studentUniversity of Technology Sydney, 15 Broadway, Ultimo NSW 2007, Australia 
Industry engagement component locationPickc Pty Ltd, Level 8, 11 York Street, Tank Stream Labs, Sydney NSW 2000, Australia 
Other locationsCSIRO Marsfield, 26 Pembroke Road, Marsfield NSW 2122, Australia 
Ideal student skillsetEssential

Solid knowledge in data science and machine learning.

Background in computer vision and/or natural language processing (NLP).

Proficiency in Python and deep learning frameworks (e.g., PyTorch/TensorFlow).

Experience with multimodal AI (vision-language models like CLIP, LLaVA).

Research skills demonstrated via publications or projects in AI or machine learning.  

Desirable

Basic knowledge of engineering/domain-specific fields (e.g., CAD, electronics, biology).

Experience with generative AI (e.g., diffusion models for synthetic blueprint generation).

Collaboration skills for interdisciplinary/industry partnerships.
Application close dateOpen until position filled
ApplyContact Shoujin Wang