Teaching

We support department’s teaching initiatives, including Digital Construction, Digitalisation in Built Environment, Advanced Measurement, and AI for Built Environment. These address key digital engineering management topics with a focus on advanced BIM, AI, and robotics aligned with our Lab's expertise.

Pedagogical Practice & Innovations

Our teaching philosophy centres on technology-enhanced, experiential, and active learning that bridges theoretical foundations, digital tools, and real-world practices for the new generation of learners.

Blended Learning 2.0: To enhance student active engagement, the Lab adopt blended learning that combines online asynchronous resources with interactive face-to-face sessions in a flipped classroom format. PI led blended learning courses and developed teaching materials for online videos and in-person lectures including storyboards, graphics and instructional videos, post-production editing, along with 19 course materials. Students are activated by reading instructional videos and come to classes with their prior study such that they can be more engaged in peer discussions and problem-solving sessions, enabling them to develop higher order thinking in classes.

Integration of Robotic Technology and Digital Tools for Experiential Learning: PI engaged students through technology applications and digital tools before lecture-led explanations of theory. Our Lab integrated frontier technologies at Centre for Digital Building Technology such as robotic scanning and digital twin into coursework, using stimulating hands-on to spark curiosity and provide context for new knowledge. Students interact with robotic dogs, drones, and augmented reality through meticulously crafted hands-on activities where students work in groups to analyse robot control strategies for scanning SDE4. The integration of digital technology in the learning process acts as a catalyst to engage students in the learning process.

Courses Taught

PF1103 Digital Construction; IPM1103 Digitalisation in Built Environment

The course introduces principles, techniques, and tools of digitalisation. Students will learn Integrated Digital Delivery, Building Information Modelling and basic robotic inspection and scanning.

PF2108 Project Cost Management

This course covers the basic principles relating to estimating of items of the work to be undertaken on projects, and tendering. Major topics are quantitative techniques in cost analysis, cost planning, approximate estimating and tendering procedures.

PF3205 Advanced Measurement

This course covers advanced aspects of building measurement including the use of IT in integrating measurement works and project management. Topics include measurement of deep excavation, substructures, underpinning, structures, additions and alterations and complex building forms.

PF3211 AI for Built Environment

This course introduces the AI applications in built environment. Students will study the fundamental background of AI, machine learning, data processing and uncertainty analysis. Major topics include AI fundamentals, classification, prediction, clustering, fault detection and diagnosis.

Teaching Awards

  • CDE Teaching Excellence Award AY2023/2024

  • CDE Teaching Excellence Award AY2022/2023

Postdoc and Student Researchers Attached to Our Lab

Researchers Supervised as Main Supervisor

  • Postdoc Research Associate and Research Fellow

    • Mingkai Li (Mar 2024 – present)

      Research Associate and Research Fellow at NUS

    • Shaobo Li (Sep 2024 – Aug 2025)

      Research Associate (Supported by CSC) at NUS

    • Asiri Weerasuriya (Aug 2018 – Mar 2019)

      Research Associate at HKUST

  • Graduate Students and Research Assistants

    • Jingxuan Li (Jan 2025 – present)
      Research Assistant
      Topic: 3D scanning and AI for defect detection and risk-based monitoring of Singapore shophouse.

    • Jey Chandar (Jan 2025 – present)
      Research Assistant
      Topic: Trajectory optimisation and semantic navigation for quadruped robots.

    • Yuanyuan Deng (Jul 2024 – Aug 2025)
      Research Assistant
      Topic: Gaussian splatting SLAM for 3D scene reconstruction of indoor built environments.

    • Yushuo Wang (Jan 2023 – Sep 2024)
      Master Researcher
      Topic: As-built 3D reconstruction of building interiors using quadruped robots and LiDAR sensors.

    • Melanie Tan (Jun 2023 – present)
      PhD Researcher (Graduate Tutor Scheme)
      Topic: Integration of LiDAR and image data for robotic operations in unmanned built environment management.

    • Hui Lin Oh (Jun 2023 – Jan 2025)
      Master Researcher
      Topic: BIM-based digital twin framework for indoor built environment monitoring and robot-assisted facility management.

    • Xiuqi Li (Aug 2022 – present)
      PhD Researcher (Ring-fenced Scholarship)
      Topic: Automated high-precision 3D BIM reconstruction for ME systems using terrestrial laser scanning and LiDAR point clouds.

    • Kexin Li (Jan 2022 – present)
      PhD Researcher
      Topic: AI-assisted automatic 3D reconstruction of large-scale building information models.

    • Xiayi Chen (Jan 2023 – Jan 2024)
      Master Researcher
      Topic: A data-driven, semantic-rich digital twin system for monitoring and analysing ACMV performance in tropical environments.

    • Qiao Zheng (May 2022 – May 2025)
      PhD Researcher
      Topic: Automated geometric quality assessment and BIM reconstruction for building and structural components using lidar data and artificial intelligence.

    • Tao Wang (Aug 2021 – Oct 2024)
      PhD Researcher (NUS Scholarship)
      Topic: Enhancing digital twins through semantic enrichment and geometric reconstruction.

    • Difeng Hu (Aug 2021 – Dec 2024)
      PhD Researcher
      Topic: AI-assisted 3D reconstruction and scene understanding for robotic navigation in indoor inspections.

  • Visiting Researchers

    • Xin Li (Sep 2023 – Sep 2024)
      Visiting PhD from Tianjin University

    • Yongjie Pan (Jan 2023 – Dec 2023)
      Visiting PhD from Southeast University

    •  Ruoming Zhai (Oct 2022 – Oct 2023)
      Visiting PhD from Wuhan University

    • Chao Xiang (Aug 2022 – Aug 2023)
      Visiting PhD from Hunan University

    • Dian Zhuang (Aug 2021 – Aug 2022)
      Visiting PhD from Southeast University

      many more …