Project members
University of Nottingham
Prof Andrew French leads the project and teaches on the image analysis and machine learning units. His area of research is computer vision and deep learning, applied to biological images.
Dr Nathan Mellor leads the practical course development for the Nottingham units. He is a post-doctoral researcher specialising in mathematical models of plants and plant tissues over a range of physical scales, including the use of many programming, machine learning and image analysis methods.
Dr Jonathan Atkinson co-leads the Introduction to Plant Phenotyping Technologies unit and teaches on the Data Capture in the Lab unit. He is a Senior Research Fellow in the School of Biosciences with research interests in plant root architecture, anatomy and root-soil interactions.
Dr Darren Wells co-leads the data capture in the lab unit. He is a Principal Research Fellow in the School of Biosciences at the University of Nottingham with research interests in addressing problems in multi-scale plant physiology using integrated phenomics approaches.
Prof Tony Pridmore is a Professor of Computer Science at Nottingham. He teaches image processing and analysis, and leads research activity in Plant Phenotyping data analysis approaches.
University of Lincoln
Prof Elizabeth Sklar leads the project on the data capture and management units. She is a research director of the Lincoln Agri-Robotics centre. Her area of research is interaction in robot teams, including multi-robot team coordination and human-robot collaboration.
Dr Andrey Postnikov leads the practical course development for the Lincoln units. He is a post-doctoral researcher specialising in robotics and multi-agent systems. His area of research is distributed systems and multi-agent control.
Dr Oorbessy Gaju co-leads the practical courses on the plant phenotyping units. She is a wheat physiologist at the Lincoln Agri-Robotics centre focusing on screening for phenotypic traits to improve wheat yield.
Prof. Simon Parsons co-leads the project on the machine learning units. His research interests centre on the design and analysis of autonomous systems. At Lincoln, he is particularly focusing on the applications of data-backed decision making, explainable artificial intelligence, market-based systems, and mobile robotics in agriculture and medicine.