Postgraduate research students

My research primarily focuses on leveraging advanced deep learning architectures to enhance the extraction of building rooftops from high-resolution orthophotos. I am particularly interested in integrating Transformer architectures, involution, and E-Unet to address the challenge of extracting precise building contours in complex urban environments. My current work involves experimenting with these models to improve the accuracy of building footprint extraction, particularly on large-scale datasets such as the Waterloo Building Dataset and the WHU Massachusetts Buildings Dataset.

Moreover, I have a keen interest in exploring the applications of 3D data in urban modeling and its broader utilization in autonomous driving systems. This includes employing 3D point cloud data and LiDAR technology to enhance scene understanding and improve the perception capabilities of autonomous vehicles. My research is progressively transitioning towards multidimensional data fusion and its applications in urban infrastructure analysis and real-time decision-making for autonomous vehicles.

Through my work, I aim to combine cutting-edge deep learning innovations with practical applications in urban environments and intelligent transportation systems, making contributions to the fields of remote sensing, 3D data analysis, and autonomous driving.

List by: Type | Date

• Professor Brian Barrett
• Dr Meiliu Wu

• 2026: Awarded the ISPRS Foundation Travel Grant (US$2,000) to support participation in the ISPRS Congress 2026 in Toronto, Canada.

• 2025: Awarded University of Glasgow Conference Support Funding (up to £630) to attend and present research at the ESA Living Planet Symposium 2025 (LPS 2025), Vienna, Austria.

•  2024: Awarded the IEEE Geoscience and Remote Sensing Society (GRSS) Travel Grant to attend IGARSS 2024, Athens, Greece.

• 2024: Awarded Research Enabling Funding from the University of Glasgow to support PhD research activities.

•  2023–2027: Recipient of a China Scholarship Council (CSC) Doctoral Scholarship supporting PhD studies in Environmental Remote Sensing at the University of Glasgow, United Kingdom.

•  2020–2022: Recipient of the Third-Class Master's Degree Scholarship, Nanjing University of Information Science and Technology (NUIST), China.

• 2019: Recognised as an Outstanding Bachelor's Degree Graduate, Nanjing University of Information Science and Technology (NUIST), China.

•  2017: Awarded the Jiangsu Government Scholarship for Overseas Study in Geographic Information Science at Saint Louis University, United States.

• Oral Presentation: ISPRS Congress 2026, Toronto, Canada, 6–11 July 2026. Cube Kernel: A Novel Approach to Enable Local Gradient Flow Across Channels in CNNs (published in the ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences).
• Poster Presentation: ESA Living Planet Symposium (LPS 2025), Vienna, Austria, 23–27 June 2025. Transformer-Based Networks for Efficient Vectorization: A Case Study of Building Rooftop Extraction.
• Poster Presentation: 2024 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2024), Athens, Greece, 7–12 July 2024. An Enhanced Trans-Involution Network for Building Rooftop Extraction from High Resolution Orthoimagery.
• Oral Presentation: International Society for Photogrammetry and Remote Sensing (ISPRS Congress 2022), Nice, France, 6–11 June 2022. A Short-Cut Connections-Based Neural Network for Building Extraction from High Resolution Orthoimagery.

2024-2025 Academic Year:

• EARTH4071 - Sedimentary Environments: Lab demonstrator with a focus on QGIS usage.
• EARTH2010 - Earth Science (2A): Lab demonstrator focusing on sediments and sustainability.
• Geography 1: Demonstrator responsible for QGIS usage and fieldwork activities.
• Geography 2: Demonstrator for Statistics and GIS Labs (Semester 1), using Excel and Python.
• Summer School 2024: Demonstrator.

2023-2024 Academic Year:

• Geography 1: Demonstrator responsible for grading assignments.

• Nominated participant in a joint Royal Society–NSFC International Exchanges proposal between the University of Glasgow and Beijing Normal University (2026), focusing on ecological resilience and environmental change in China's dryland regions.

• Research Assistant, GoTrees Project, University of Glasgow (2025–2026). Contributing to the development of deep learning methods for tree classification from airborne LiDAR point clouds, including tree segmentation, dataset preparation, and hierarchical classification.

• High Performance Computing (HPC) experience using the University of Glasgow MARS cluster, including A40 and A100 GPU resources for large-scale deep learning experiments in remote sensing and point cloud analysis.

• CVPR 2025 AI Art Gallery: Although my CVPR paper submission wasn’t accepted, a research visualization (an intermediate result from my work) was selected for the CVPR 2025 AI Art Gallery: https://thecvf-art.com/project/zhimeng-he/