Haoran (Nate) Liang, MEng, E.I.T.
Faculty of Engineering - Civil and Environmental Engineering Dept
Contact
Term Admin Professional
Faculty of Engineering - Civil and Environmental Engineering Dept
- hliang7@ualberta.ca
Overview
Area of Study / Keywords
Automation in Construction Multi-Agent Systems
About
Haoran Liang 梁皓然
Structural Engineering MEng @ University of Alberta | Research Assistant @ SITE Lab
I am a structural engineering graduate with a Master’s degree from the University of Alberta and a Bachelor’s from Wuhan University. I currently work as a research assistant in the Smart Infrastructure Technologies (SITE) Research Group.
My research focuses on integrating structural engineering with AI, particularly in automating structural analysis and design workflows using large language models. I am deeply interested in multi-agent systems, model coordination, and domain-specific reasoning for structural engineering.
I'm always open to discussions on structural design, AI-powered engineering workflows, or potential collaborations. Feel free to get in touch!
Scholarly Activities
Research - Peer Reviewer – Advanced Engineering Informatics
2026-09-13 to 2026-09-20
Served as a peer reviewer for Advanced Engineering Informatics, providing an independent scholarly assessment of a submitted manuscript and constructive feedback to support the journal's editorial decision-making process.
Featured Publications
Haoran Liang, Mohammad Talebi-Kalaleh, Qipei Mei
Automation in Construction. 2026 December; 10.1016/j.autcon.2026.107215
Haoran Liang, Yufa Zhou, Mohammad Talebi Kalaleh, Qipei Mei
2025 October; 10.48550/ARXIV.2510.11004
Haoran Liang, Mohammad Talebi Kalaleh, Qipei Mei
arXiv. 2025 April; 10.48550/arxiv.2504.09754
View additional publications
Research Students
Currently accepting undergraduate students for research project supervision.
I am looking for students who have experience with large language models (LLMs), knowledge of context engineering, multi-agent systems, and real-world structural engineering workflows, and are interested in applying LLM technologies to automate real-world structural engineering processes.