Professor | Ji Zhou | Asia Growth Partners

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Name	Ji Zhou
Contact Information	Ji.Zhou@njau.edu.cn
Language ability	English, Chinese
Province	Jiangsu

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Name

Ji Zhou

Contact Information

Ji.Zhou@njau.edu.cn

Language ability

English, Chinese

Province

Jiangsu

University/Lab Affiliation and Title	Nanjing Agricultural University
Faculty	academy for adyanced interdisciplinary studies
Academic Background & Achievements	2006-10 to 2011-07 PhD in Computer Science: University of East Anglia 2003-09 to 2005-07 MSc in Information Systems: University of East Anglia 1995-09 to 1999-07 Bachelor's in Engineering: Shanghai University of Engineering Science
Work Experience	2020-01 to Present - National Institute of Agricultural Botany, Cambridge Crop Science - Head of Data Sciences, Director of Agricultural Innovation Lab, Doctoral Supervisor 2017-10 to Present - Nanjing Agricultural University - Distinguished Professor, Lab Director, Doctoral Supervisor 2016-11 to Present - University of East Anglia - Associate Professor (Computer Vision, Machine Learning), Doctoral Supervisor 2014-11 to 2019-11 - Earlham Institute and John Innes Centre - Researcher, Lab Director, Doctoral Supervisor 2011-03 to 2014-10 - The Sainsbury Laboratory - Senior Postdoctoral Researcher 2005-08 to 2009-03 - Aviva Insurance Group - e-broking System Analyst, Senior Software Project Consultant 2002-07 to 2003-07 - Singapore Informatics Group (Shanghai Branch) - IT Trainer, Multimedia Software Developer 1999-08 to 2002-07 - Shanghai Yucai High School - Computer Teacher, Multimedia Software Developer
Awards	2021: Member of the BBSRC Review Committee (Computational Biology, Committee B) 2020: Invited Member of the Innovate UK Project Review Committee 2019: Fellow of the Royal Society of Biology (FRSB) 2018: Member of the Royal Society of Biology (MRSB) 2018: Finalist at the Royal Norfolk Agricultural Technology Innovation Exhibition 2017: Nominated for the Most Promising Research Industry in Eastern England by Eastern Daily Press 2016: UK/US Global Scientific Grant by UK and US Foreign and Science Ministries 2013: Selected as an Outstanding Young Scientist to present at the UK House of Commons 2010: Received UK Higher Education Teaching Qualification

University/Lab Affiliation and Title

Nanjing Agricultural University

Faculty

academy for adyanced interdisciplinary studies

Academic Background & Achievements

2006-10 to 2011-07 PhD in Computer Science: University of East Anglia
2003-09 to 2005-07 MSc in Information Systems: University of East Anglia
1995-09 to 1999-07 Bachelor's in Engineering: Shanghai University of Engineering Science

Work Experience

2020-01 to Present - National Institute of Agricultural Botany, Cambridge Crop Science - Head of Data Sciences, Director of Agricultural Innovation Lab, Doctoral Supervisor
2017-10 to Present - Nanjing Agricultural University - Distinguished Professor, Lab Director, Doctoral Supervisor
2016-11 to Present - University of East Anglia - Associate Professor (Computer Vision, Machine Learning), Doctoral Supervisor
2014-11 to 2019-11 - Earlham Institute and John Innes Centre - Researcher, Lab Director, Doctoral Supervisor
2011-03 to 2014-10 - The Sainsbury Laboratory - Senior Postdoctoral Researcher
2005-08 to 2009-03 - Aviva Insurance Group - e-broking System Analyst, Senior Software Project Consultant
2002-07 to 2003-07 - Singapore Informatics Group (Shanghai Branch) - IT Trainer, Multimedia Software Developer
1999-08 to 2002-07 - Shanghai Yucai High School - Computer Teacher, Multimedia Software Developer

Awards

2021: Member of the BBSRC Review Committee (Computational Biology, Committee B)
2020: Invited Member of the Innovate UK Project Review Committee
2019: Fellow of the Royal Society of Biology (FRSB)
2018: Member of the Royal Society of Biology (MRSB)
2018: Finalist at the Royal Norfolk Agricultural Technology Innovation Exhibition
2017: Nominated for the Most Promising Research Industry in Eastern England by Eastern Daily Press
2016: UK/US Global Scientific Grant by UK and US Foreign and Science Ministries
2013: Selected as an Outstanding Young Scientist to present at the UK House of Commons
2010: Received UK Higher Education Teaching Qualification

Areas of Focus	Multi-scale crop phenotyping AI-based phenotypic analysis Crop genomics and breeding
Publications	SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination, Colmer J, O'Neill CM, Wells R, Bostrom A, Reynolds D, et al., Penfield S, Zhou J, 2020 室内植物表型平台及性状鉴定研究进展和展望, 徐凌翔, 陈佳玮, 丁国辉, 卢伟, 丁艳锋, 朱艳, 周济, 2020 An exploration of deep learning based phenotypic analysis to detect spike regions in field conditions for UK bread wheat, Alkhudaydi T, Reynolds D, Griffiths S, Zhou J, De La Iglesia B, 2019 Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture: a case study of lettuce production, Bauer A, Bostrom A, Ball J, Applegate C, Laycock S, Kirwan J, Zhou J, 2019 What is cost-efficient phenotyping – optimizing costs for different scenarios, 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, 2019 CropSight: a scalable open data and distributed data management system for crop phenotyping and IoT based crop management, Reynolds D, Ball J, Bauer A, Griffiths S, Zhou J, 2019 植物表型组学: 发展、现状与挑战, 周济, Tardieu F, Pridmore T, 等, 2018 Speed breeding: a powerful tool to accelerate crop research and breeding, Watson A, Ghosh S, Williams M, Cuddy WS, Simmonds J, Rey M-D, Hatta MAM, Hinchliffe A, Steed A, Reynolds D, et al, 2018 Leaf-GP: An Open and Automated Software Application for Measuring Growth Phenotypes for Arabidopsis and Wheat, Zhou J, Applegate C, et al., 2017 CropQuant: the next-generation automated field phenotyping platform for breeding, crop research and agriculture, Zhou J, Reynolds D, et al., Griffiths S*, 2017 An automated quantitative image analysis approach for identifying microtubule patterns, Faulkner C#, Zhou J#, Evrard A, Bourdais G, MacLean D, Häweker H, Garcia M, Bakal C, Eckes P, Robatzek S, 2017 Genomic innovation for crop improvement, Bevan M. W., Uauy C., Wulff B. B. H., Zhou J., Krasileva K., Clark M. D., 2017 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 CalloseMeasurer: a novel software solution to measure callose deposition and callose patterns, Zhou J, Spallek, T., Faulkner, C., Robatzek, S., 2013 Spatio-temporal cellular dynamics of Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting, Beck, M., Zhou J, et al., Robatzek, S., 2012

Areas of Focus

Multi-scale crop phenotyping
AI-based phenotypic analysis
Crop genomics and breeding

Publications

SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination, Colmer J, O'Neill CM, Wells R, Bostrom A, Reynolds D, et al., Penfield S*, Zhou J*, 2020
室内植物表型平台及性状鉴定研究进展和展望, 徐凌翔, 陈佳玮, 丁国辉, 卢伟, 丁艳锋, 朱艳, 周济*, 2020
An exploration of deep learning based phenotypic analysis to detect spike regions in field conditions for UK bread wheat, Alkhudaydi T*, Reynolds D, Griffiths S, Zhou J*, De La Iglesia B, 2019
Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture: a case study of lettuce production, Bauer A, Bostrom A, Ball J, Applegate C, Laycock S, Kirwan J, Zhou J*, 2019
What is cost-efficient phenotyping – optimizing costs for different scenarios, 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*, 2019
CropSight: a scalable open data and distributed data management system for crop phenotyping and IoT based crop management, Reynolds D, Ball J, Bauer A, Griffiths S, Zhou J*, 2019
植物表型组学: 发展、现状与挑战, 周济*, Tardieu F, Pridmore T, 等, 2018
Speed breeding: a powerful tool to accelerate crop research and breeding, Watson A, Ghosh S, Williams M, Cuddy WS, Simmonds J, Rey M-D, Hatta MAM, Hinchliffe A, Steed A, Reynolds D, et al, 2018
Leaf-GP: An Open and Automated Software Application for Measuring Growth Phenotypes for Arabidopsis and Wheat, Zhou J*, Applegate C, et al., 2017
CropQuant: the next-generation automated field phenotyping platform for breeding, crop research and agriculture, Zhou J*, Reynolds D, et al., Griffiths S*, 2017
An automated quantitative image analysis approach for identifying microtubule patterns, Faulkner C#, Zhou J#, Evrard A, Bourdais G, MacLean D, Häweker H, Garcia M, Bakal C, Eckes P, Robatzek S, 2017
Genomic innovation for crop improvement, Bevan M. W., Uauy C., Wulff B. B. H., Zhou J., Krasileva K., Clark M. D., 2017
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
CalloseMeasurer: a novel software solution to measure callose deposition and callose patterns, Zhou J, Spallek, T., Faulkner, C., Robatzek, S., 2013
Spatio-temporal cellular dynamics of Arabidopsis flagellin receptor reveal activation status-dependent endosomal sorting, Beck, M., Zhou J, et al., Robatzek, S., 2012

Phenotyping Ai Genomics Breeding Crop Data Fusion Machine Learning Remote Sensing Agriculture Innovation

Xu Shan - Nanjing Agricultural University

Shichao Jin - Nanjing Agricultural University

Frédéric Baret - Nanjing Agricultural University

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