Teaching

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

Pedagogical Practice and Innovations

Pedagogical practice and innovations that has taken include:

Blended Learning 2.0: PI lead the development of blended learning courses for Project Cost Management. Collaborating with TEL-Evangelists from the Centre for Instructional Technology (CIT) and the Centre for Development of Teaching & Learning (CDTL), we develop teaching materials for online videos and in-person lectures including storyboards, graphics, over 880 minutes of promotional and instructional videos, post-production editing, along with 19 course materials. Students are activated in advance by reading instructional videos and come to classes with their prior study and question such that they can be more actively engaged in peer discussions and problem-solving sessions, enabling them to dive deeper in classes.

Integration of Technology and Digital Tools for Experiential Learning: PI prioritises engaging students through technology applications and digital tools before lecture-led explanations of theory. In Digital Construction, a guided tour in Centre for 5G Digital Building Technology is provided, where students interact with robotic dogs, drones, and augmented reality through meticulously crafted hands-on activities. For Advanced Measurement, I introduce advanced 3D modelling technology with software exercises based on real buildings, demonstrating how 3D modelling can automate measurement. The integration of digital technology in the learning process acts as a catalyst for student interest and engagement, while establishing connections between theory and practice to solidify their understanding of the new subject.

Teaching Awards

CDE Teaching Excellence Award AY2022/23

Courses Taught

PF1103 Digital Construction; IPM1103 Digitalisation in the Built Environment

This course is designed to provide an overview of the concepts and applications of digital construction. The concepts of computational thinking will form the theoretical basis of this course and will be incorporated to teach how computation can be used to accomplish a variety of goals. The major topics include basics of computational thinking, basic coding, and applications in digital construction such as Building Information Modelling (BIM).

PF2108/IPM2104 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. The principles governing the pricing of items and building up rates for items of work are also covered.

PF3205 Advanced Measurement

This course covers the more advanced aspects of building measurement found in projects 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 the built environment. Students will study the fundamental background of AI, machine learning, data processing and uncertainty analysis. Major topics include fundamentals of AI, classification, prediction, clustering, fault detection and diagnosis.

Postdoc and Student Researchers Attached to Our Lab

Postdoc Research Associates

[1] Mingkai Li (Mar 2024 – present)
Research Associate at NUS

[2] Shaobo Li (Sep 2024 – present)
Research Associate (Visiting) at NUS

[3] Asiri Weerasuriya (Aug 2018 – Mar 2019)
Research Associate at HKUST

Graduate Students and Research Assistants

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

[2] Yuanyuan Deng (Jul 2024 – present)
Research Assistant
Topic: LiDAR-SLAM and Gaussian splatting algorithms for indoor environments.

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

[4] Melanie Tan Ing Suan (Aug 2022 – present)
PhD Researcher (Graduate Tutor Scheme)
Topic: Integration of LiDAR and image data for robotic operations in unmanned built environment management.

[5] Hui Lin Oh (Aug 2022 – Jan 2024)
Master Researcher
Topic: BIM-based digital twin framework for indoor built environment monitoring and robot-assisted facility management.

[6] 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.

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

[8] Xiayi Chen (Jan 2022 – Jan 2024)
Master Researcher
Topic: A data-driven, semantic-rich digital twin system for monitoring and analysing ACMV performance in tropical environments.

[9] Qiao Zheng (Aug 2021 – present)
PhD Researcher
Topic: Automatic geometric quality assessment of construction works using LiDAR data and AI techniques.

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

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

Visiting Researchers

[1] Xin Li (Sep 2023 – Sep 2024)
Visiting PhD from Tianjin University

[2] Yongjie Pan (Jan 2023 – Dec 2023)
Visiting PhD from Southeast University

[3] Ruoming Zhai (Oct 2022 – Oct 2023)
Visiting PhD from Wuhan University

[4] Chao Xiang (Aug 2022 – Aug 2023)
Visiting PhD from Hunan University

[5] Dian Zhuang (Aug 2021 – Aug 2022)
Visiting PhD from Southeast University

[6] Ting Liu (Aug 2021 – Dec 2021)
Visiting PhD from Tianjin University