• Research

Ji Zhou

Phenomics Project Leader


Contact details:

  • +44 (0) 1603 450 089 (EI)
  • +44 (0) 1603 450 612 (JIC) 




My team focuses on developing novel high-throughput bioimage informatics algorithms and software solutions using computer vision, feature extraction and machine learning. Since my joint appointment between EI and JIC, I have been leading a number of key plant phenomics research projects including JIC's high-throughput field phenotyping platform based on HPC infrastructures at EI, cost-effective infield phenotyping device (CropQuant) to monitor wheat growth, and large automated screening platforms (SeedGerm) to quantify seed germination and seedling vigour. My research endeavours to overcome the phenotyping bottleneck in agricultural and crop research.

I am currently in close collaboration with several world-leading researchers at JIC, CAS (Chinese Academy of Sciences) and IBERS on crop growth, crop interaction with environmental stress, quantitative phenotypic description, and machine learning based algorithms to measure key crop traits. Furthermore, I'm collaborating with industrial leaders such as Syngenta, G’s Growers and Intel.

Prior to my career at EI, I worked in industry for nearly a decade – initially as a bilingual IT professional in Shanghai, China, then a systems analysis and project consultant at Norwich Union (Aviva UK). Between 2011 and 2014, I was appointed as a post-doctoral scientist at The Sainsbury Laboratory, Norwich. During this period, I was leading the development of high-throughput bioimage analysis algorithms in order to extract meaningful data from large phenotypic datasets acquired by HCS (high content screening system), confocal microscopes and digital cameras.

Agri-Tech Innovations at Norwich Research Park

My laboratory works across several research projects in IoT in agriculture, remote sensing, and machine learning based crop analysis and growth prediction.


A developmental framework for complex plasmodesmata formation revealed by large-scale imaging of the Arabidopsis leaf epidermis.

Fitzgibbon, J., Beck, M., Zhou, J., Faulkner, C., Robatzek, S., and Oparka, K. (2013).  The Plant Cell: 25: 57–70.

CalloseMeasurer: a novel software solution to measure callose deposition and recognise spreading callose patterns.

Plant methods: 8: 49.Zhou, J., Spallek, T., Faulkner, C., and Robatzek, S. (2012).

Spatio-temporal cellular dynamics of the Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting.

Beck, M., Zhou, J., Faulkner, C., MacLean, D., and Robatzek, S. (2012). The Plant Cell: 24: 4205–19.


2013: Selected SET for Britain presenter to appear in House of Commons, the Parliamentary and Scientific Committee UK 

2008: Regional runner-up (East Anglia) in IET Present around the World, UK