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Prof Chunbo Luo

Associate Professor in Computer Science


Telephone: 01392 725725

Extension: (Streatham) 5725


My current research interests lie in the novel data science methods for remote sensing data acquisition and processing (machine learning, autonomous vehicles). These scientific investigations have real-world applications in areas such as natural disaster relief and marine observation. Examples include the detection of algal blooms, tracking of marine carbon flux, and detection of marine oil spills, among others. My work greatly benefits from collaborative research with leading research institutes, including the Plymouth Marine Laboratory, the Met Office, and the National Oceanographic Centre.


  • We have 3 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! 
  • A magazine paper 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. 
  • 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: (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. 
  • 欢迎2023年优秀学生申请PhD奖学金(包括CSC scholarship等, 50个全额奖学金机会),研究课题(Machine learning and intelligent sensing methods for Earth observations; Interpretable methods for remote sensing data collection and processing etc.)可参考下面的课题等。
  • 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.
  • 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 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.  


  • Research Manager: EU Horizon 2020 project: Intelligent and Sustainable Aerial-Terrestrial IoT Networks
  • Theme lead:  Remote Sensing, Institute for Data Science and Artificial Intelligence (IDSAI)
  • Steering commitee member of NERC NEODAAS


Some industrial projects I have worked on include:

  • A software pipeline to detect very small objects from infrared images, PI. In collaboration with UWS and Thales, the outcome of this project won a Knowledge Transfer Award. It developed and successfully demonstrated deep learning models to detect small objects in images with high accuracy. This project is a winner of the 2018 Scottish Knowledge Transfer Award!
  • Benchmark multi-stage malware attacks with a novel dataset and machine Learing models. This project is funded by EPSRC and BT through the ICASE stream. The dataset is available now (Email to apply access). 

Current projects

  • Integrating UAVs and Social Sensing for Timely Flooding Warning in Coastal Areas, Royal Society, 2023-2025, PI. 
  • Intelligent Satellite Remote Sensing for Real-Time Accurate Geological Hazard Analysis, Royal Society, 2023-2025, CoI
  • UKRI KTN. Automated insurance rebuilds cost estimate for residential and commercial properties, with RCA, Ref: 10031767, 10/2022-09/2024.  
  • EU H2020. INITIATE: Intelligent and Sustainable Aerial-Terrestrial IoT Networks, 101008297,  01/2022-12/2025, CoI.
  • NERC. SENSUM: smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement, NE/V003402/1, 10/2020-09/2023, CoI
  • EPSRC Industrial CASE with BT.Multi-stage Cyber Attack detection using Machine Learning Approaches, Project No. 19000043, 10/2019-09/2024, PI

Previous projects (from 2015)

  • DeepWater: Remote sensing and DEEP learning for early warning of WATER quality hazards, Plymouth Marine Laboratory and ESA (Dragon 4), £60,869.57, 09/2018-07/2022, PI
  • NERC. BigFoot: BIG data methods for improving windstorm FOOTprint prediction, NE/P017436/1, £1,530,230, 2017-2021, CoI
  • Thales-Challenge Low-pixel Automatic Target Detection and Recognition (ATD/ATR), Scottish Funding Council with CENSIS and Thales, £139K, 2015-2016, PI, (Scottish Funding Council Knowledge Transfer Medal)
  • KTP (Knowledge Transfer). Research on Key Communication Technologies for UAVs to Transmit High-Definition Video, Contract No: H02016050002CG, £54,794, 01/08/2017 – 31/07/2018, PI
  • KTP (Knowledge Transfer). High-Performance Distributed Algorithms and Key Technologies for Processing SDN Big Data, Huawei Technologies, Contract No: YBN2016080110, £223,200, 08/2017 – 10/2021, CoI
  • ESRC IAA. Building Digital Identities: A Scoping Study, Social Policy Network, 2017-2018, CoI. LinkReport
  • Royal Society of Edinburgh. Flood Detection and Monitoring using Hyperspectral Remote Sensing from Unmanned Aerial Vehicles, £19,950K, 2016-2018, CoI
  • Feasibility study on a fully deployable resilient flooding predicting, monitoring and response system, Exeter EMPS ADR funding, 2016-2017, PI.
  • China UK Technology Innovation Centre Workshop 2016 (with Prof G Parr, University of East Anglia, and other 7 UK universities, Prof W Chen of Tsinghua University, Shanghai Jiaotong University and other 3 China research institutes, as well as Prof N Azarmi BT and other 4 industrial partners). Link
  • EU Horizon 2020. SELFNET Framework for Self-organized Network Management in Virtualized and Software Defined Networks, €6.8M, 2015-2017, Co-I.
  • 2016 Exeter-Tsinghua Outward Mobility Academic Fellowship
  • EPSRC Digital Economy: A Pilot Study on a Fully Deployable Cooperative Unmanned Aerial Vehicles System for Flooding Prediction, Monitoring and Response Services, PI.
  • Royal Society. Research on Multiple UAV Cooperation for Marine Oil Spill Detection, PI. 

Some recent talks

  • 2021 UK-China collaborative workshop: AI for Climate, Environment and Sustainability 
  • 2021 PML-Exeter joint workshop on Change Detection for Very High Resolution (VHR) Remote Sensing 
  • 2020 18th IEEE ISPA Machine Learning empowered Future Network Workshop Keynote Talk: Machine Learning for Communication and Network Data Processing
  • 2019 BT Thought Leadership Talk Forum

PhD projects(博士研究和奖学金机会)

Highly motivated postgraduate students are welcome to apply for PhDs. I am offering to supervise self-funded PhD students in the areas of:

  • Machine/deep learning methods
  • Image and data processing
  • Intelligent autonomous vehicles

Previous group members

  • Dr James Nightingale - Teaching fellow, University of Strathclyde
  • Dr Huaizhong Zhang - Senior Lecturer, Edge Hill University
  • Dr Qin Zhang - Associate Professor, Qingdao Agricultural University
  • Dr Leonhard Menz - Head of Process, Porsche AG
  • Dr Yang Mi - Postdoc RA, The Hong Kong Polytechnic University
  • Mr Stephen Goult - Machine Learning Development Software Engineer, Spirent Communications