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Dr Chunbo Luo

Senior Lecturer in Computer Science


Telephone: 01392 725725

Extension: (Streatham) 5725



  • 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)


My current research interests are around networked and cooperative unmanned vehicles (UxV including UAV, UGV, UWV etc.) including their networking, machine learning methods and applications in environment, particularly in marine science, supported by research collaboration with leading research institutes including the Plymouth Marine Laboratory and National Oceanographic Centre, and scientific discoveries on marine data processing for algae-bloom detection, marine carbon flux tracking and marine oil spill detection etc. 

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:

  • EU H2020, INITIATE: Intelligent and Sustainable Aerial-Terrestrial IoT Networks, Project co-coordinator
  • NERC, SENSUM:  smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement, CoI
  • With PML, ESA Dragon 4, DeepWater: Remote sensing and DEEP learning for early warning of WATER quality hazardsExeter PI
  • NERC, BigFoot: BIG data methods for improving windstorm FOOTprint prediction, CoI
  • 2015-2017 Royal society: Energy-Efficient High-Performance Computing Architecture Solutions for Powerful Big Data Processing, CoI
  • Feasibility study on a fully deployable resilient flooding predicting, monitoring and response system, ADR funding.
  • 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
  • 2016 ESRC: IAA Social Policy Network: Building Digital Identities: A Scoping Study, CoI LinkReport
  • 2016 Exeter-Tsinghua Outward Mobility Academic Fellowship
  • Royal Society of Edinburgh: Flood Detection and Monitoring using Hyperspectral Remote Sensing from Unmanned Aerial Vehicles, Co-I.
  • 2015 EU H2020: SELFNET, UWS Co-I.
  • RCUK Digital Economy: A Pilot Study on a Fully Deployable Cooperative Unmanned Aerial Vehicles System for Flooding Prediction, Monitoring and Response Services, PI.
  • Royal Society, NSFC: 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 (e.g. reinforcement learning, federated learning) for future networked vehicles
  • Image processing on remote sensing data collected by drones or satellites
  • Autonomous vehicles cooperation and swarm intelligence

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