Areas of expertise

  • Bioinformatics
  • Biomedical Engineering
  • Biosensors & Diagnostics
  • Computing, Simulation & Modelling
  • Counter-IED
  • Defence Sensors
  • Environment and Health
  • Food Safety
  • Industrial Automation
  • Instrumentation, Sensors and Measurement Science
  • Monitoring and Environmental Informatics
  • Nanotechnology
  • Sensor Technologies
  • Soil


Peter Yuen obtained his First Class Honour in Physics and subsequently a PhD in Semiconductor Physics from the Imperial College, University of London, in 1987. Peter was accredited Fellows of the Institute of Physics (FInstP) and the Institute of Mathematics and its applications (FIMA) in 2001. Peter had about 10 years of working experience with corporate laboratory such as the BAE Systems, the Defence Evaluation Research Agency (DERA) and the Asahi Kasei (Japan) between 1997-2007 period. Peter is currently a Reader in remote sensing & electro-optics at Cranfield University since 2013. Peter has 92 peer-reviewed journal and conference papers publications in semiconductor physics, sensors, defence science, Electro-Optics, image processing including remote sensing, hyperspectral imaging, machine vision and machine learning disciplines, with over 640 journal citations from his recent 5 year publications since 2016 (H-index 11). Peter has contributed 5 of his best journal papers towards the REF2020 entry, and he is an active peer reviewer for high impact factor journals such as the IEEE Transactions on Geoscience and Remote Sensing (TGRS), Neural Computing and Applications (NCAA), Optics & Laser Technology (JOLT), Optical Engineering (OE), MDPI’s Remote Sensing, Computers and Electronics in Agriculture (COMPAG) etc. Peter’s current research includes computer vision using statistical machine learning technique, as well as artificial intelligence deep learning methods for the detection of 'difficult' targets from heavily cluttered and camouflaged backgrounds.

Research opportunities

Peter’s team has strong collaboration with universities in the UK and world-wide, for the R&D of remote sensing technology specifically for agricultural, environmental, industrial and security applications. Collaborators are mostly academic institutes in the UK and Far-East (China, India & Singapore), geared for the development of next generation sensor and sensing system for surveillance and world-monitoring applications towards the clean air objective. We have strong link with a few agricultural universities in China (e.g. Nanjing Agricultural University, Shanxi Agricultural University, Jiangsu University etc) and in India/Pakistan. Collaborations are taken place through joint projects funded by government bodies such as EPSRC/NERC, Royal Society, DSTL and Newton Fund etc. We welcome full time, part time and exchange researchers and students to work with us either on-site or remotely.      

Current activities

Current research topics in the team include :

  • Electro-optics research for the development of efficient snap-shot multispectral imaging system.
  • Compressive imaging algorithm development to achieve high degree of spectral reconstruction accuracy from the snap-shot multispectral imaging data.
  • Hyperspectral scene simulations and their validations: to acquire an end-to-end realistic hyperspectral scene simulation capability within the next 5 years.
  • Reduction of dimensionality in hyperspectral imaging through band selections for the enhancement of efficacy and efficiency of detecting ‘difficult’ targets.
  • Data driven optimisation of deep learning artificial intelligence methodology for the detection and classification of high dimensional data.
  • Efficacy, efficiency, robustness and flexibility of deep learning AI methodology in comparison with statistical machine learning algorithms for target detections in high dimensional hyperspectral imaging data.
  • Efficiency of X-ray imaging using coded aperture compressive sensing technique.
  • Robustness and efficiency of deep learning for the analysis of big data which consists of multi-modal of imaging data.
  • Atmospheric correction of hyperspectral scene in the wide spectrum ranging from visible to near infra-red and far-infrared domains.
  • Illumination independent targets detection methodology development.
  • Diffuse optical imaging for biomedical applications such as in-vivo blood oxygenation assessment, tumour classification, affective computing.
  • Spectral constancy including shadow removal.
  • Tomography including the development of x-ray back scatter imaging system.
  • Hyperspectral diffused optical tomography for target recognition in undersea environments.
  • Colour constancy for improving image visualisation and target detection.
  • Automatic target recognitions using cortex-like machine vision in the spectral and spatial domains.


  • Electro Magnetic Remote Sensing Defence Technology Centre
  • Systems Engineering for Autonomous Systems (SEAS) Defence Technology Centre
  • Home Office
  • Centre for the Protection of National Infrastructure (CPNI)
  • Defence Science and Technology Laboratory (DSTL)
  • European Defence Agency (EDA)
  • QinetiQ
  • Lockheed Martin
  • British Transport Police
  • SELEX 
  • EPSRC-Technology Strategy Board
  • Procter & Gamble (P&G)
  • Counter Terrorism Centre (CTC)
  • Roke Manor Research
  • 2Excel Aviation
  • Rothamsted Research
  • Nanjing Agricultural University
  • Shanxi Agricultural University


Articles In Journals

Conference Papers