Ruiyan ZHENG

Ruiyan ZHENG

Ph.D. Student @ NUS
zhengruiyan@u.nus.edu

About

I am a Ph.D. student in the Cognition X Lab at the National University of Singapore (NUS). My research focuses on semantic digital twins for on-site construction rescheduling and reconfiguration. I received my Master's degree from Dalian University of Technology (DUT) in June 2025, where I worked on construction scheduling optimization.

I am broadly interested in digital construction, construction management, and AI-enabled decision support. I am always open to research collaborations. Feel free to reach out!

Interests

  • Digital Twin in the Built Environment
  • Construction Scheduling and Resource Allocation
  • LLM Application in Construction Sector
  • Ontology and Knowledge Graph

Education

National University of Singapore
Dalian University of Technology
  • M.Eng in Construction Management, Sep. 2022 - Jun. 2025
  • Supervisor: Prof. Zhongfu Li
Qingdao University of Technology
  • B.Eng in Quantity surveying, Sep. 2018 - Jun. 2022

Publications

Showing 5 selected publications

Research methodology linking document parsing, ontology-governed knowledge graph generation and updates, and hybrid vector–graph question answering.
Fig. 2 Research methodology
Selected

A Synergized LLM-KG Framework for Domain Knowledge Cognition

Ruiyan Zheng, Jinying Xu
Proceedings of the 43rd ISARC, Singapore, pp. 2032–2038, 2026.
Three-stage framework for evaluating how on-site industrialized construction technologies contribute to industrialization goals: identify technologies and goals, determine goal weights with DEMATEL, and rank contributions using hesitant fuzzy prospect theory.
Fig. 1 Evaluation framework
Selected

Evaluating the contribution of on-site industrialized construction technologies towards industrialization goals

Shengbin Ma, Zhongfu Li, Ruiyan Zheng*
Journal of Building Engineering, 109, 113022, 2025.
Four-level digital twin collaboration diagram linking Human DT, Hospital DT, Public Health DT, and the Global healthcare emergency management network through health data, computing power, directives, and recommendations.
Fig. 6 Four-level DT collaboration
Selected

Leveraging digital twin for healthcare emergency management system: Recent advances, critical challenges, and future directions

Ruiyan Zheng, S. Thomas Ng, Yuyang Shao, Zhongfu Li, Jiduo Xing
Reliability Engineering & System Safety, 261, 111079, 2025.
Lean-based mixed-flow production scheduling framework: lean-construction scenario modeling, mixed-flow modeling, and multi-objective waste reduction combine order and resource information to produce an optimal schedule and performance measures.
Fig. 2 Framework of LMPS
Selected

Proposing a Lean-Optimized Scheduling Model of Mixed-Flow Prefabricated Component Production in Off-Site Construction

Ruiyan Zheng, Zhongfu Li, Long Li, Yudan Dou, Mengqi Yuan, Xianfei Yin
Journal of Construction Engineering and Management, 150(8), 04024088, 2024.
MOOG research methodology: mixed-flow precast production and group technology inform embodied-carbon, efficiency, production-area, and processing-time constraints; an adjusted NSGA-II framework generates and empirically evaluates the schedule.
Fig. 3 MOOG research methodology
Selected

Group technology empowering optimization of mixed-flow precast production in off-site construction

Ruiyan Zheng, Zhongfu Li, Long Li, Shengbin Ma, Xiaodan Li
Environmental Science and Pollution Research, 31(8), 11781–11800, 2024.

Selected Honors & Awards

  • Outstanding Paper Award on CRIOCM 2023
  • Outstanding Master's Thesis of Dalian University of Technology
  • National Scholarship for Graduate Students
  • National Scholarship for Undergraduate Students
  • First Prize of China Undergraduate Mathematical Contest in Modeling (CUMCM)
  • 2020 Honourable Mention of COMAP's Interdisciplinary Contest in Modeling (ICM)

Publication figure

Publication figure

Select a publication figure to view it at full size.

1 of 5