Agriculture meets AI

In this seminar, Professor Scott Chapman will discuss the digital and predictive agriculture technologies that are studied at UQ.

Abstract

Agriculture is one of the earliest sciences developed by human society. Innovations in agriculture, or adopted by agriculture, allowed us to feed and clothe ourselves with less and less labour. Allowing people to diversify away from growing their own food enabled multiple leaps in creating our modern world. Artificial intelligence and the data sciences are enabling ‘Agriculture 4.0’. In 2020, agrifood tech startups raised more than $30 billion in investment. Many of these innovations are deployed in agriculture research, supporting new sustainable solutions that keep us fed.

In this seminar, Professor Scott Chapman will discuss the digital and predictive agriculture technologies that are studied at UQ.

Host

Professor Zi (Helen) Huang

Dr. Huang is a Professor and ARC Future Fellow in School of ITEE, The University of Queensland. She received her BSc degree from Department of Computer Science, Tsinghua University, China, and her PhD in Computer Science from School of ITEE, The University of Queensland in 2001 and 2007 respectively. Dr. Huang's research interests mainly include multimedia indexing and search, social data analysis and knowledge discovery. She has published 200+ papers in prestigious venues, and is currently an Associate Editor of The VLDB Journal, ACM Transactions on Information Systems (TOIS), Pattern Recognition Journal, etc and also a member of the VLDB Endowment Board of Trustees.

Dr. Huang has received 2016 Chris Wallace Award from Computing Research and Education (CORE) Australasia for a notable breakthrough or a contribution of particular significance in Computer Science, and Women in Technology (WiT) Infotech Research Award 2014, Queensland. She was also a recipient of the Excellence in Higher Degree by Research Supervision Award, University of Queensland, 2018. Dr. Huang is the Data Science Discipline Leader, UQ.

Speaker

Professor Scott Chapman

Professor Scott Chapman is a crop physiologist working on genetic and environmental effects on the physiology of field crops, particularly in drought-affected regions.

He uses quantitative approaches (crop simulation and statistical methods) and phenotyping (aerial imaging by drones, etc.) to integrate the understanding of interactions of genetics, growth and development, and the bio-physical environment on crop yield.

In recent years, his collaborations have expanded more generally into various applications in digital agriculture from work on canopy temperature prediction for irrigation decisions through to applications using ‘deep fake’ image analysis to assist plant breeders.