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Dr Chunbo Luo

Senior Lecturer in Computer Science

Email:

Telephone: 01392 725725

Extension: (Streatham) 5725

Dr. Chunbo Luo is a Senior Lecturer in Computer Science within the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK.

 

Proud of Mingtao Fu, who has made an extraordinary donation of 3000 facemasks to help Hospiscare doctors and nurses in Devon during the COVID-19 crisis (Exeter postgraduate researcher is Hospiscare Hero). Mingtao is jointly supervised by Engineering expert Dr Miying Yang and me.

 

Research

His research interests focus on developing model-based and machine learning algorithms to solve practical problems such as wireless networking, unmanned aerial vehicles, and remote sensing.

Some industrial projects I have worked on include:

  • Machine learing for malware prediction, funded by EPSRC and BT for a PhD project, Principal Investigator, 2019-2023. In collaboration with Selina Wong from BT, to predict and mitigate future threats from malware.
  • Deep learning for image processing, Principal Investigator, 2015-2017. In collaboration with UWS, the outcome of this project won a knowledge transfer award. It developed and successfully demonstrated deep learning models to enhance images, a winner of the 2018 Scottish Knowledge Transfer Award! 

Some recent research projects include:

  • 2021-2024, EU H2020, INITIATE: Intelligent and Sustainable Aerial-Terrestrial IoT Networks, CoI
  • 2020-2022, NERC, SENSUM:  smart SENSing of landscapes Undergoing hazardous hydrogeologic Movement, CoI
  • 2018-2023, with PML, ESA Dragon 4, DeepWater: Remote sensing and DEEP learning for early warning of WATER quality hazardsPI
  • 2017-2021, NERC, BigFoot: BIG data methods for improving windstorm FOOTprint prediction, CoI
  • 2017-2019, 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, 2016-2017, 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
  • ESRC: IAA Social Policy Network: Building Digital Identities: A Scoping Study, CoI, 2017. LinkReport
  • Exeter-Tsinghua Outward Mobility Academic Fellowship, 2016. 
  • Royal Society of Edinburgh: Flood Detection and Monitoring using Hyperspectral Remote Sensing from Unmanned Aerial Vehicles, Co-I, 2015-217.
  • EU H2020: SELFNET, UWS Co-I, 2015-2017.
  • RCUK Digital Economy: A Pilot Study on a Fully Deployable Cooperative Unmanned Aerial Vehicles System for Flooding Prediction, Monitoring and Response Services, PI, 2015-2016.
  • Royal Society, NSFC: Research on Multiple UAV Cooperation for Marine Oil Spill Detection, PI, 2013-2015. 

 

Prospective PhD and Master students

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

  • Visual data processing
  • Remote sensing images
  • Algorithms
  • Deep learning and its real-world applications
  • The theories underpin machine learning

PhD studentships may be offered, e.g. 

  • China Scholarship Council and University of Exeter Full PhD Scholarships Link
  • More PhD Studentship opportunities at Exeter. Link

 

Teaching

  • Algorithms that changed the world;
  • Outside the box, Computer Science research and applications;
  • The C family languages

 

Third year/MSc student project examples

  • Patients Waiting Time Prediction for NHSquicker, Yuchen Zhu, Computer Science MSc project award winner!
  • Video search (searching an object such as a red car from video clips)
  • Infrared video analyses of egg spawning of weakly electric blunt nose knifefishes
  • Block-chain based systems for combating VAT fraud, and trustful weather data management
  • Fall detection of senior people at care homes using deep learning methods 
  • Prediction and Visulisation of Air Quality in the UK