Highly Skilled Experts

Contact person: Release date: 2018-04-27




2006-2011: PhD in Computer Science, University of East Anglia (UEA), Norwich UK     

2003-2005: MSc in Information Systems, UEA, Norwich UK    

1995-1999: BEng in Computer Controlling, Shanghai University of Engineering Science, China


Employment History (including career breaks where relevant)

2017–present: Professor of Crop Phenomics at Nanjing Agricultural University (NAU), China

2016–present: Senior lecturer of computer vision (Hon.), UEA, UK

2014–present: Project leader, Earlham Institute (EI, previously known as The Genome Analysis Centre, TGAC, co-funded by John Innes centre, JIC), Norwich Research Park (NRP), UK

2011–2014: Postdoctoral research fellow, The Sainsbury Laboratory (TSL), Norwich UK

2005–2009: Lead systems analyst & Project consultant, IT Solutions and e-Services platform, Norwich Union (Aviva Global Insurance), UK

2002–2003: Software engineer & bilingual IT trainer, Singapore Informatics Group (Shanghai)

1999–2002: Multimedia developer & IT teacher, Yucai Educational Group, Shanghai China


Honours and Prizes

2017: The East of England’s strongest scientific industries, Agri-Tech (Eastern Daily Press, UK)

2017: Best scientific presentation at XIX International Botanical Congress

2016: UK/US global scientific travel grant awarded by Science & Innovation, Foreign Office UK

2013: Selected as a presenter by the UK Parliamentary & Scientific Committee to present in House of Commons in SET for Britain 2013


Panels and Committees

UK EMPHASIS – European Infrastructure for multi-scale Plant Phenomics and Simulation

PhenomUK – Crop phenotyping in the UK: from Sensors to Knowledge

UEA/JIC PhD and MSc supervisory & examination board (computer vision, machine learning)

Invited reviewer for Biotechnology and Biological Sciences Research Council (BBSRC, UK) and Engineering and Physical Sciences Research Council (EPSRC) funding applications

Associated reviewers for a number of research journals for phenotyping, plant phenomics, image analysis, and machine-learning.


Selected Invited Academic/Industrial Talks and Lectures (in last 12 months)

03/2018: Session keynote, the 2nd Asia Pacific Plant Phenotyping Conference (Chinese Plant Phenotyping Network, CPPN, and NAU) – From data to knowledge – multi-scale phenotypic analyses to extract meaningful information from big plant phenotyping datasets.

01/2018: Keynote, Image Analysis for Plant Sciences (International Plant Phenotyping Network, IPPN, and Uni. of Nottingham) – From Field to Cells: multi-scale phenomics in crop improvement

12/2017: Session keynote, The International conference for field phenotyping and modelling for cultivation (Japan Science and Technology Agency, JST, and Tokyo University) – Automated and scalable crop phenotyping to facilitate breeding, crop research and digital agriculture.

12/2017: Keynote, International Plant Phenomics Symposium (Chinese Academy of Sciences, CAS) – Dynamic interactions between genetic diversity, phenotypic analyses, and environment.

10/2017: Invited speaker, Internal –omics seminar (Enza Zaden, Netherlands). 

11/2017: Invited presenter, REAP 2017 (Agri-Tech East and RCUK) – CropQuant robot: Shelia.

07/2017: Invited speaker, XIX International Botany Conference (IBC).

06/2017: Keynote, National Knowledge Transfer Network (KTN) Agri-Food Conference (KTN, Newton, and Innovate UK).

03/2017: Invited speaker, NAU crop phenomics conference.


Grants and projects in the UK (in last two years, as a PI since 2016)

2018: UK-China Partnering Award (BBSRC), PI – Forge a long-term UK-China relationship in phenotyping, Agri-Tech and crop research for Rice and Wheat

2018: NRP Seed Fund (NRP), Co-PI – A GPU-accelerated deep-learning based Agri-Tech robotic system for CropQuant robot. 

2018: ATCNN (Agri-Tech China: Newton Network+) focus award, PI – Identify key wheat growth stages based on large aerial images in the UK and China.

2018: Medical Research Council, Co-I – Phenome UK: UK crop phenotyping.

2017: Bayer AG G4T focus award, PI – Develop image-based machine learning technologies to enable trait measurements of spikes per unit area and spikelet number and anther extrusion for hybrid wheat seed production breeding at Bayer.

2018: Increased efficiency and sustainability (BBSRC, designing future wheat programme), named sub-package leader in WP1. 

2017: BBSRC Follow-on Pathfinder award, PI – CropQuant technologies.

2017: BBSRC Responsive mode award, Co-I – Genetic improvement of rice seed vigour.

2017: UK Science & Innovation Network, PI – UK/US phenotyping innovations.

2017: Syngenta and EI industrial collaboration, PI – A machine-learning based seed germination software solution for screening commercial seeds.  


Publications according to Google Scholar

17 research articles, 2 chapters, 2 patents (UKIPO, Agri-Tech CropQuant, GB1709756.9; UKIPO SeedGerm, 81233GB1 under revision), citations: 411 (since 2013), h-index (since 2013): 9.


Selected and accepted publications (last 5 years, bold names are members of my laboratory)

1. Reynolds D, Baret F, Welcker C, Bostrom A, Ball J, Cellini F, Lorence A, Chawade A, Khafif M, Noshita K, Mueller-Linow M, Zhou J*, Tardieu F* (2017). What is cost-efficient phenotyping – optimizing costs for different scenarios. Plant Science (accepted).

2. Alharbi N., Zhou J.*, Wang W.J.*, (2018). Automatic Counting of Wheat Spikelets From Wheat Growth Images. IEEE Journal of Pattern Analysis and Applications, Pattern Recognition and Methods, 7:346-355.

3. Watson A, Ghosh S, Williams M, Cuddy WS, Simmonds J, Rey M-D, Hatta MAM, Hinchliffe A, Steed A, Reynolds D, et al (2018). Speed breeding: a powerful tool to accelerate crop research and breeding. Nature Plants, 4:23–29.

4. Zhou J*, Applegate C, Alonso AD, Reynolds D, Orford S, Mackiewicz M, Griffiths S, Penfield S, Pullen N (2017). Leaf-GP: An Open and Automated Software Application for Measuring Growth Phenotypes for Arabidopsis and Wheat. Plant Methods, 13:117.

5. Faulkner C^, Zhou J^, Evrard A, Bourdais G, MacLean D, Häweker H, Garcia M, Bakal C, Eckes P, Robatzek S. (2017). An automated quantitative image analysis approach for identifying microtubule patterns. Traffic, 11(2): 109-117.

6. Bevan M. W., Uauy C., Wulff B. B. H., Zhou J., Krasileva K., Clark M. D. (2017). Genomic innovation for crop improvement. Nature, 543:346–354.

7. Meteignier L. V.^, Zhou J.^, Cohen M., Bhattacharjee S., Goretty M., Chan C., Robatzek S., Moffett P. (2016). NB-LRR signaling induces translational repression of viral transcripts and the formation of RNA processing bodies through mechanisms differing from those activated by UV stress and RNAi. Journal of Experimental Botany, 67(4).

8. CRK Consortium (2015). Large-scale phenomics identifies primary and fine-tuning roles for CRKs in responses related to oxidative stress. PLOS Genetics: 11(7).

9. Beck M^, Zhou J^, Faulkner C, Robatzek S (2014). High-throughput imaging of plant immune responses, Plant-Pathogen Interactions: 27(11): 67-80.

10. Fitzgibbon, J., Beck, M., Zhou, J., Faulkner, C., Robatzek, S., and Oparka, K. (2013). A developmental framework for complex plasmodesmata formation revealed by large-scale imaging of the Arabidopsis leaf epidermis. The Plant Cell: 25: 57–70.

11. Zhou, J., Spallek, T., Faulkner, C., and Robatzek, S. (2013). CalloseMeasurer: a novel software solution to measure callose deposition and callose patterns. Plant methods: 8: 49.

12. Beck, M., Zhou, J., Faulkner, C., MacLean, D., and Robatzek, S. (2012). Spatio-temporal cellular dynamics of the Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting. The Plant Cell: 24: 4205–19.


^ Joint first author   * Corresponding or co-corresponding author 

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