SIGMA Research Group emblemSIGMA Lab
Working space of the SIGMA research group
Sigma emblem of the research group

SIGMA Research Group

Smart Infrastructure & GIS Management with AI Lab

Artificial intelligence for safe and sustainable urban infrastructure

Recognised under Decision 1053/QĐ-TĐHTPHCM dated 23 July 2026

Members
12
Research directions
04
Scientific publications
69
Years of recognised operation
03

Who we are

An interdisciplinary group on artificial intelligence for urban infrastructure

To grow into a strong research group that develops interdisciplinary machine and deep learning methods for identifying, predicting and managing geotechnical and urban infrastructure risk on GIS and BIM foundations, and that delivers internationally competitive models, tools and technology products linked to education and technology transfer for smart, sustainable cities.

Interdisciplinary application of artificial intelligence, machine learning and deep learning to geotechnical engineering, urban infrastructure management, project management and geographic information systems. Machine and deep learning is the core method across every project of the group.

Learn about the group

Office plaque of the SIGMA research group
Recognition decision:
1053/QĐ-TĐHTPHCM
Date signed:
23 July 2026
Signed by:
Rector Huynh Quyen
Operating period:
09/2026 - 08/2029
Host unit:
Department of Urban Infrastructure Management, Faculty of Geodesy, Cartography and Civil Engineering, Ho Chi Minh City University of Natural Resources and Environment (HCMUNRE)

Scientific focus

Four core research directions

The four directions share machine learning and deep learning as their core method, connecting below-ground geotechnical data with above-ground infrastructure and project management data.

Research output

Latest publications

Ask SIGMA

Ask a question in plain language to find the publications closest to your topic.

  • Application of Handheld LiDAR Technology in Tree Detection and Measurement: A Case Study of Pine Forest in Da Lat, Lam Dong Province, Vietnam

    Tran Ngoc Huyen Trang, Phan Nguyen Viet, Nguyen Ngoc Bang, Nguyen Huu Duc, Le Van Trung, Vo Le Phu

    IOP Conference Series: Earth and Environmental Science, Vol. 1633, 2026

    • Conference paper
    • Indexed in Scopus
  • Công tác kiểm kê đất đai và thành lập bản đồ hiện trạng sử dụng đất năm 2024 sau khi sáp nhập đơn vị hành chính: Nghiên cứu tại xã Phước Long, tỉnh Cà Mau

    Mai Thị Duyên

    Tạp chí Xây dựng, Số 5, 90-93, 2026

    • Journal article
  • Enhancing the Urban Agglomeration Management Effectiveness combining UAVs, Deep Learning, and WebGIS in Ho Chi Minh City, Vietnam

    Tran Ngoc Huyen Trang, Le Van Trung, Vo Le Phu

    Geomatics and Environmental Engineering, 20(5), 2026

    • Journal article
    • Indexed in ESCI
  • Estimating carbon sequestration in urban trees using UAV-derived CHM and Deep Learning-based crown extraction: A climate-responsive greenery planning approach

    Tran Ngoc Huyen Trang, Le Van Trung, Vo Le Phu

    Lecture Notes in Civil Engineering (Springer), GIS IDEAS 2026, 2026

    • Conference paper
    • Indexed in Scopus
  • Explainable Deep Learning for Settlement Prediction and Risk Classification of Transportation Infrastructure on Soil Foundations

    Luu Le Minh, Hiep Nguyen Anh, Truong Dang Xuan

    Transportation Infrastructure Geotechnology, Volume 13, article number 167, 2026

    • Journal article
    • Journal quartile Q2
    • Indexed in SCIE
    • Indexed in Scopus
    • Impact factor: 2.600
  • Extracting building footprints from UAV imagery for urban digital transformation in Ho Chi Minh City

    Tran Ngoc Huyen Trang, Le Van Trung, Vo Le Phu

    Journal of People, Plants, and Environment, 29(1), 2026

    • Journal article
    • Indexed in Scopus

People

Group leader and core member

Activities

Latest news

Work with SIGMA Lab

The group welcomes collaboration with government departments, consulting and construction firms, research institutes and international research groups on data collection, joint publication, graduate training and technology transfer.