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Dr Chunbo Luo

Senior Lecturer in Computer Science


Telephone: 01392 725725

Extension: (Streatham) 5725


  • 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. 
  • 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.
  • 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.  
  • A funded PhD project: Monitoring of landslide hazards with wireless sensor networks and machine learning, supervised by Dr Georgie Bennett, Dr Kyle Roskilly, and Dr Chunbo Luo, click to apply
  • A funded PhD project: Machine learning for geospatial intelligence, supervised by Dr Isabel Sargent, Ordnance Survey and Dr Chunbo Luo click to apply
  • A funded PhD project: Detecting the impacts of river plumes in coastal waters from satellite imagery using machine learning, NERC GW4+ DTP PhD studentship for 2023 Entry.
  • Congratulations to our new successful grant: Optimising Energy Demand in Rural Communities via Precision Agriculture Technology (SWIFT), led by LENKÉ: Space & Water Solutions Ltd
  • Our special issue is accepting paper now: Prediction and (Back)Tracking of Marine Oil Spill Drift and Diffusion, in the journal Frontiers in Marine Science. Link
  • We are delighted to report one KTP project will be funded by UKRI (2-year postdoc job - click to apply)
  • Congratulations to Jiawei, Peigeng, Zhipeng for receiving the CSC-Exeter PhD project grants!  
  • Our IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Special Issue: Cooperative Perception for Computer Vision in Remote SensingClick to submit your work NOW for early review and publication!
  • Our new MSc Data Science (Apprenticeship) programme is recruiting (Submit your application).
  • Many congratulations to the excellent REF result achieved by the department and university! 


  • Research Manager: EU Horizon 2020 project: Intelligent and Sustainable Aerial-Terrestrial IoT Networks
  • Programme director: MSc Data Science Professional
  • Theme lead:  Remote Sensing, Institute for Data Science and Artificial Intelligence (IDSAI)
  • Member of the High Performance Computing and Networking (HPCN) group led by Prof Geyong Min


My current research interests are around cooperative autonomous vehicles and their sensing data for environment applications (networked UxVs, including drones, ground vehicles, surface vessels etc.). The focus is on intelligent data processing methods (machine learning etc) and networking (wireless networks, smart networks etc.). The scientific discoveries have the following real-world applications including natural disaster relief, marine observation, and Net Zero. Some examples include algae-bloom detection, marine carbon flux tracking and marine oil spill detection etc. My work benefits significantly from research collaboration with leading research institutes including the Plymouth Marine Laboratory, the Met Office, and National Oceanographic Centre.

Nature has demonstrated the importance of cooperation with evidences from cooperative species out compete selfish species in many ways. One good example is from the study of African wild dogs: Lycaon pictus. Their communal hunting (74% success) is proved to be a success by outperforming lion (32%) which is thought to be the ultimate predator in the world (from my PhD thesis). 

Some industrial projects I have worked on include:

  • To develop Machine Learing models to predict malware trends, funded by EPSRC and BT for a PhD project, Principal Investigator. In collaboration with Selina Wong from BT.
  • Detect very small objects from infrared images, Principal Investigator. 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!

Some recent research projects include:

  • UKRI KTN. Automated insurance rebuilds cost estimate for residential and commercial properties, with RCA, £166,793. Ref: 10031767, 10/2022-09/2024.  
  • Innovate UK. Developing a Decision Support Tool for Mini-Grid Energy Developers, £279,132 (Exeter £80,501), Energy Catalyst, 04/2023 – 03/2024, Exeter PI, with LENKÉ: Space & Water Solutions Ltd.
  • EU H2020. INITIATE: Intelligent and Sustainable Aerial-Terrestrial IoT Networks, 101008297, Euro: 952,200, 01/2022-12/2025, Research manager and CoI
  • NERC. SENSUM: smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement, NE/V003402/1, £1.2M, 10/2020-09/2022, CoI
  • EPSRC Industrial CASE with BT.Multi-stage Cyber Attack detection using Machine Learning Approaches, Project No. 19000043, £130,900, 10/2019-09/2024, PI
  • 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 and research applicants

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

  • Machine learning methods (e.g. reinforcement learning, federated learning) for networked autuonomous vehicles in disaster relief
  • Image and data processing for sensing data collected by drones or satellites 
  • Cooperation and swarm intelligence of networked autonomous vehicles in disaster relief

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