Dr Wanli Ma

About

I am a Postdoctoral Research Fellow at the University of Cambridge, where I have been based since January 2025. My research focuses on the intersection of artificial intelligence (AI) and satellite remote sensing for earth observation. In my current role, I work on AI-enabled large-scale disaster damage assessment (such as blasts, floods, and fires) as part of the EPSRC-funded MicroBlast project. Prior to joining Cambridge, I completed my PhD in Computer Science at Cardiff University in 2024. Working within the Visual Computing Group under the supervision of Dr Oktay Karakus (Remote Sensing) and Prof Paul Rosin (Computer Vision, Fellow of the IAPR), my doctoral thesis explored 'Towards Minimal Supervision for Semantic Segmentation of Remote Sensing Imagery.' Previously, I received a Master's degree with Distinction in Image and Video Communication and Signal Processing from the University of Bristol (2021), where my dissertation focused on "Ship Wake Detection in SAR Imagery Using Dual-Tree Complex Wavelet Transform (DT-CWT)".

My research focuses on advanced computer vision, with particular emphasis on "minimal supervision" approaches aimed at reducing the labelling burden in training machine learning models. These include semi-supervised learning, active learning, and multi-modal fusion. I am interested in bridging the gap between theoretical AI and its practical applications in satellite remote sensing imagery. In particular, my work aims to develop solutions for pressing real-world challenges, including rapid large-scale disaster damage assessment (floods, hurricanes, and explosions), marine monitoring, and urban infrastructure detection. Beyond remote sensing, I have a strong interest in applying computer vision to robotics and industrial automation. In this space, I have successfully developed and commercialised automated facilities for the manufacturing sector.

Skills

Recent News & Activities

Publications

Google Scholar

Oral & Poster Presentations

• Oral Presentation: The International Geoscience and Remote Sensing Symposium (IGARSS), Brisbane, Australia, 03-08 Aug 2025
• Oral Presentation: The International Geoscience and Remote Sensing Symposium (IGARSS), Athens, Greece, 07-12 Jul. 2024
• Oral Presentation: The British Machine Vision Conference (BMVC), Aberdeen, UK, 20-24 Nov. 2023
• Oral Presentation: The International Geoscience and Remote Sensing Symposium (IGARSS), Pasadena, US, 16-21 Jul. 2023
• Poster: The British Machine Vision Association (BMVA) Summer School, Norwich, UK, 11-15 Jul. 2022
• Poster: Vision Researchers Colloquium 2022, Cardiff, UK, 4 Jul. 2022
• Poster: Special Event: The British Machine Vision Association (BMVA) 3 Day Symposium, Manchester, UK, 4-6 Apr. 2022
• Oral Presentation: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Toronto, CA (Virtually), 6-11 Jun. 2021

Teaching and Supervision

Teaching

I have over two years of teaching experience in the computer science discipline, including
• Postgraduate module “Machine Learning”, enrollment: 150+ students(Since 2022)
• Undergraduate module “Data Structures", enrollment: 150+ students (Since 2024)
• Summer courses “Python Programming” and “Machine Learning and Its Applications” (Since 2025)
  • Teaching two courses, each enrolling over 30 undergraduate students annually.
  • Python Programming: data type & structures, function, file I/O.
  • Machine Learning and Its Applications: focus on practical and theoretical aspects of machine learning, including supervised/unsupervised learning, neural networks, and model evaluation.
  • Machine Learning and Its Applications: guided students through a series of hands-on projects applying AI techniques to detect and analyse urban buildings from remote sensing imagery.

Supervision

• Diya Thomas, postgraduate at the University of Cambridge. Vision Foundation Models for Disaster Damage Assessment. (2026)
• Ningxin He, undergraduate at the National University of Singapore. Machine Learning Approaches for Earthquake-induced Building Damage Assessment. (2025)
• Xiaoyu Zhang, undergraduate at the University of Cambridge. Reinforcement Learning based Control for Robotic Hoisting in Construction Environments (2025)
• Henry Booth, postgraduate at Cardiff University. Marine Debris Detection Using Deep Learning Networks. Now at the Met Office. (2023)
• Naga Padala, postgraduate at Cardiff University. Integrating PCA, HSV, and Raw Remote Sensing Data via Deep Learning for Land Cover Classification. (2022)

Collaboration

• University of Sheffield (2025 – present): Collaborating on blast-loading-informed building damage assessment, with the Sheffield team providing blast-loading simulations for the 2020 Beirut explosion area.
• Chinese Academy of Sciences (2025 - present): Co-developed landslide detection methods based on computer vision and satellite remote sensing imagery.
• Cardiff University (2025 - present):
  • Knowledge distillation from various foundation models for semantic segmentation of remote sensing imagery, with regular meetings to discuss technological developments.
  • Robot operation and hoisting: collaborating with Cardiff, which provides a simulation environment for soft-object manipulation, while we develop object state prediction and reinforcement learning–based control algorithms.
• AI for Good Lab – Microsoft Research (2023-2024): A collaboration focused on geospatial analytics, applying AI to extract actionable insights and structured information from spatial data, including satellite and aerial imagery. Specifically, we explored automated methods for selecting the most informative coresets from large-scale datasets for land cover mapping to reduce the workload for labelling.
• The German Aerospace Centre (DLR) (2023-2026):
  • Collaborated on coreset selection, with DLR providing large-scale satellite datasets for label cover mapping.
  • Collaborated on AI for physics-informed building damage assessment, with DLR providing building damage data for the 2020 Beirut Explosion.

Academic Services

• Reviewer for artificial intelligence journals: IEEE Transactions on Image Processing (T-IP), IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), Neurocomputing, Digital Signal Processing (DSP).
• Reviewer for remote sensing journals: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS), International Journal of Applied Earth Observation and Geoinformation (JAG). GIScience & Remote Sensing (GRS), Remote Sensing (RS), Scientific Reports (SR).
• Session Chair: "Remote Sensing Image Reconstruction, Processing, and Enhancement" in IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2025.