Professor Chunbo Luo

2025 PhD Studentships: Exeter University is offering 50 CSC funded projects. 留学基金委(CSC)和Exeter共提供50个博士全奖项目，欢迎同学们联系和申请。我会直接指导申请流程，包括材料准备、优秀的样本、未来的科研选题等。今年建议题目是AI/Foundation Model、信号处理、IoT等方向。欢迎同学们联系 （Deadline: 1/12/2025)。详细信息

Prof Luo's research focuses on machine learning and intelligent sensing methods to address complex environmental challenges, e.g., collecting and processing Earth observations and remote sensing data. Please visit my lab page (Intelligent Networking and Sensing for Environment - ISE Lab) for more details of our research, code and datasets. 

My scientific investigations aim to contribute to natural hazard and disaster mitigation, and environment protection. Specific examples include the deep learning methods for detecting algal blooms captured in high resolution remote sensing data, and marine oil spills etc. My work greatly benefits from collaborative research with leading research institutes, including the Plymouth Marine Laboratory, the Met Office, IBM etc. I am a recipient of the ESI Highly Cited Papers recognition. Some of our impactful papers are as follows:

• Earth Foundation Model: REOBench: Benchmarking Robustness of Earth Observation Foundation Models, accepted in NurIPS 2025. Paper
• Earth Foundation Model: A Sentinel-3 Foundation Model for Ocean Colour, https://arxiv.org/html/2509.21273v1 (Try the Code; read the IBM podcast)

Prof Luo is an IEEE Senior Member, and has organized and/or chaired (with other leading researchers) over 14 conferences/workshops, including the 17th IEEE International Conference on Big Data Science and Engineering; The 20th International Conference on Computer and Information Technology; The 10th IEEE International Conference on Big Data and Cloud Computing; The 4th IEEE International Conference on Data Science and Systems; The 14th International Symposium on Pervasive Systems, Algorithms, and Networks; International Symposium on Advances in Data Science and Technologies; International Symposium on Advanced Topics in Pervasive Computing and Networking Technologies; The Machine Learning for Earth Observations in Exeter(2023, 2024, 2025); The BMVC workshop on Machine Vision for Earth Observation (2023, 2024, 2025); The 21st IEEE International Conference on Embedded Software and Systems (ICESS).

• I am looking for self-funded PhD students who have a strong motivation to freely explore the relevant research directions (e.g. AI, foundation models, multi-modality learning) within my research areas, with a strong coding/math background.  
• We are organsing a journal special issue in IET Image Processing: Computer Vision for Earth Observation and Environmental Monitoring. Submit your paper here. 

Admin & Services

• Deputy Director of Research and Impact at Department of Computer Science
• Steering commitee panel member of NERC NEODAAS

News - 2025

• Our paper was accepted at AAAI 2026: Achieving Equilibrium under Utility Heterogeneity: An Agent-Attention Framework for Multi-Agent Multi-Objective Reinforcement Learning, congratulations to Zhuhui and all authors!
• We are developing an AI-driven Earth observation change detection tool for the Saudi Arabia's NOEM regreen project.  
• We received AIRR's generous sponsorship for 8 Nvidia H200 GPUs. Thanks to the funder!
• Our paper was accepted at NurIPS 2026: REOBench: Benchmarking Robustness of Earth Observation Foundation Models. Congratulations to Dr Xiang Li & Dr Tianjin Huang and all authors!
• I am organising and chairing the 21st IEEE International Conference on Embedded Software and Systems (ICESS), to be held in Exeter, England, UK, 13-15 August, 2025.  
• I am supporting proposal preparation for the EU MSCA Postdoctoral Fellowships. We have access to the ISCA 32 A100 GPUs for the training and testing of novel machine learning models. Welcome to get in touch with your CV.
• Congratulations to all for the EU Horizon funded project on AI and networking technologies for environmental observations (INSTANT, 1.18M Euro).
• I am pleased to announce the successful EPSRC IAA project (PI) on geofoundation models for high-resolution wildfire detection.
• I am organising and chairing the Machine Learning for Earth Observation (ML4EO) conference, to happen on 18-20 June 2025. The conference will include hands-on training on Foundation models by IBM, NEODAAS training on how to use ML models to process real-world remote sensing data, academic and industry presentations, research integrity talks, and Keynote speakers from The Met Office, Alan Turing Institute, Cambridge, IBM, Exeter.
• Congratulations to Jiahao Liu (Tsinghua University UG) for the successful application of Exeter-CSC PhD scholarship. 
• Congratulations to Abhi, Qinglan, Elizabeth, on the successful defense of their PhD thesis.
• Our paper published in IEEE Transactions on Intelligent Transportation Systems (JCR Q1): Intelligent Offloading Balance for Vehicular Edge Computing and Networks. Congratulations to all. 
• Our paper published at the flagship IEEE Transactions on Geoscience and Remote Sensing (JCR Q1): MambaHSISR: Mamba Hyperspectral Image Super-Resolution". Congratulations to all. 
• Our paper presented on the ICML workshop on Machine learning for remote sensing: OSDMamba: Enhancing Oil Spill Detection from Synthetic Aperture Radar Images Using Selective State Space Model. Congratulations to the authors.
• Our paper published on IEEE Vehicular Magazine (JCR Q1) on the Federated learning methods for future autonomous vehicles: Decentralized Federated Learning for Intrusion Detection in 6G-based UxV Networks (DOI: 10.1109/MVT.2024.3520907). 
• Our paper published on Remote Sensing of Environment (JCR Q1), focusing on explainable machine learning methods for landslide detection: An interpretable attention-based deep learning method for landslide prediction based on multi-temporal InSAR time series: A case study of Xinpu landslide in the TGRA

News - 2024 Archive

• PhD Studentship: Exeter University is offering 50 CSC funded projects. 留学基金委(CSC)和Exeter共提供50个博士全奖项目，欢迎同学们联系和申请。我直接指导申请流程，包括材料准备，优秀的样本，未来的科研选题等。我们课题组今年建议题目是AI/大模型、多模态、diffusion model等方向 Click here to apply!
• Our exciting paper on foundation models in segmenting vehicular data can be found on IEEE Trans. Intelligent Vehicles (DOI: 10.1109/TIV.2024.3461651) 
• Try my supervised project completed by Haoyang on classifiying land covers using deep learning models, and compare the changes happend in history. The system demonstration is here.
• Machine learning for Earth Observation Workshop 2024 will be held in Exeter on 24/25 June. Click here to register the workshop!
• We have 2 papers focusing on machine learning for remote sensing image processing accepted in IEEE International Symposium on Geoscience and Remote Sensing 2024 (IGARSS 2024).
• We have 2 papers on the smart sensor networks for land movement detection and machine learning methods for environment data processing accepted in EGU 2024! Congratulations to all!
• Our paper published in IEEE Network Magazine is avaialbe: Ubiquitous and Robust UxV Networks: Overviews, Solutions, Challenges, and Opportunities
• Our remote sensing data processing and machine learning pipeline with code tools will be available soon.

News archive - 2023

• Congratulatios to the final workshop for the NERC funded SENSUM project (5 Dec 2023), Thanks to all speakers.
• Our BMVC 2023 workshop on Machine Vision for Earth Observations is today (24 Nov 2023) Click here to attend! Many thanks to all the organizing committees for their outstanding efforts.
• EPSRC PhD studentships: https://www.exeter.ac.uk/study/pg-research/funding/phdfunding/epsrc-dtp-studentships/ (If you are interested in AI/ML for Earth Observations, please send me an email to co-write a proposal.)
• We are proud to announce the 17th IEEE International Conference on Big Data Science and Engineering and joint conferences, to be held in Exeter from 1 November to 3 November 2023.
• Pleased to announce one NERC funded GW4+ PhD studentship opportunity: Click
• Congratulations to our data science professional programme - we will be the primary apprenticeship provider for the BBC.
• 4 top journal papers (Remote Sensing of Environment (IF 10.1), Science of the Total Environment (IF 10.15), IEEE Trans on Industry Informatics (IF 10.2), IEEE Internet of Things Journal (IF 11.7)) were recently accepted.
  • Coastline detection in satellite imagery: A deep learning approach on new benchmark data (with code and data)
  • Intelligent Content Pre-caching Scheme for Platoon-based Edge Vehicular Networks
  • See the Wind: Wind Scale Estimation with Optical Flow and VisualWind Dataset (with code and data, paper)
  • Federated Learning for Distributed IIoT Intrusion Detection using Transfer Approaches
• A new project on Machine learning methods for high resolution aerial sensing data processing to be funded by the EPSRC iCASE with OS.
• The 17th IEEE International Conference on Big Data Science and Engineering (BigDataSE-2023) and sister conferences are calling for papers.
• Our project A rapid assessment tool for Woodland Creation investment to the competition Feasibility studies for Artificial Intelligence solutions will be funded.
• Our EU Horizon project (REFINE) for air quality monitoring using drones is going to be funded (May 2023).
• Our Google.org AI for the Global Goals project with PML scientists passed the interview stage.
• We are excited to announce the workshop on "Machine learning for remote sensing" to be held in the University of Exeter, on 20-21 April 2023.
• Our projects "Integrating UAVs and social sensing for timely flooding warning in coastal areas" and "Robust and Agile Monitoring and Communication in Remote Sensing for Efficient Geological Hazard Prevention" to be funded by the Royal Society in 2023.
• Our papers were accepted in the European Geosciences Union (EGU ) 2023 conference, to be held in Vienna, Austria, on 23 April. (Smart sensors to detect movements of cobbles and large woody debris dams. Insights from lab experiments, by Alessandro Sgarabotto et al.; Smart cobbles and boulders for monitoring movement in rivers and on hillslopes by Kyle Roskilly et al.)
• Glad to receive the student feedback report for my module ECM3428 Algorithms that changed the world, which received overwhelmingly positive feedback and has a total score of 4.72 out of 5. Enjoyed teaching our talented students again.