BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Plant Success - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.plantsuccess.org
X-WR-CALDESC:Events for Plant Success
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Australia/Melbourne
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20250405T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20251004T160000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20260404T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20261003T160000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20270403T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20271002T160000
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Australia/Melbourne:20260713T080000
DTEND;TZID=Australia/Melbourne:20260715T170000
DTSTAMP:20260429T234822
CREATED:20260223T040740Z
LAST-MODIFIED:20260427T010345Z
UID:5779-1783929600-1784134800@www.plantsuccess.org
SUMMARY:Winter School in AI and Predictive Agriculture
DESCRIPTION:The Winter School in AI and Predictive Agriculture is a free event to share the collective learnings of experts from The University of Queensland in the use of AI and predictive analytics in Agriculture and Sustainability. The event will be held on 13-15 July 2026 at The University of Queensland St Lucia Campus\, Brisbane and will feature seminars\, case studies and hands-on workshops. \nThe Winter School aims to: \n\nBuild capacity in applied AI for agriculture\, especially amongst PhD students\, EMCRs and industry participants;\nProvide participants with practical skills\, not just knowledge;\nDemonstrate AI as an enabler to make standard agricultural technologies more accessible.\n\nA high level agenda is below\, you can submit an expression of interest to attend one or more of the events: \n\nMonday 13 July: AI Toolkit and Foundations\nAll day: Lecture\, online or in person. Morning tea and lunch will be provided for in person attendees.\nAttendees will learn the foundations of AI in an accessible way to support the applied case studies and hands‑on workshops in the following days. Topics will include: \n\nIntro to Neural Networks\nAI Models and Embeddings\nTransformers and LLMs\nAgentic AI\nAI tools deployment\n\n\nTuesday 14 July: Phenotyping\nAM: Lecture\, online or in person. Morning tea will be provided for in person attendees.\nAttendees will explore how the AI Toolkit can be applied to advanced predictive phenotyping through expert seminars and real-world case studies. Topics will include: \n\nSensors and point clouds\nMachine learning for phenotyping\nFoundation models for crops\nHigh throughput platforms and 3D digital twins\nUAV image data processing\n\nPM: Hands-on workshop\, in person only (spaces limited). Lunch will be provided.\nParticipants will apply the methods introduced on real-world problems. \n\nWednesday 15 July: Genomic prediction\nAM: Lecture\, online or in person. Morning tea will be provided for in person attendees.\nAttendees will learn how AI methods can be leveraged for genomic prediction via expert seminars and applied case studies. Topics will include: \n\nFundamentals of Genotype-to-Phenotype models\nEnsemble models\nGraph Neural Networks applied to genomic prediction\nMarker selection using biological priors and networks\nAgentic coding to build a genomic prediction pipeline\n\nPM: Hands-on workshop\, in person only (spaces limited). Lunch will be provided.\nParticipants will apply the methods introduced on real-world problems. \nSpaces for hands-on workshops are strictly limited. \nWe are currently seeking expressions of interest for this event\, please complete the EOI form here if you would like to participate > \nScientific and Technical Committee\nDavid Kainer\nSenior Research Fellow\, The University of Queensland\, ARC Centre of Excellence for Plant Success \nGenomic prediction and graphs. \n  \nAlex Wu\nSenior Research Fellow\, Queensland Alliance for Agriculture and Food Innovation \nField-level design/prediction\, optimisation and machine learning with crop models to explore G×E×M interactions and design optimal crop ideotypes. \nLiqi Han\nResearch Fellow\, Queensland Alliance for Agriculture and Food Innovation \nCrop Digital Twins\, High Performance Computing\, Artificial Intelligence\, High Throughput Phenotyping. \n  \nBrodie Lawson\nPostdoctoral Researcher\, Queensland University of Technology\, ARC Centre of Excellence for Plant Success \nCrop growth modelling across scales\, including plant signalling\, cell-growth and physiology. Gaussian process regression as a surrogate to true modelling to create fast models for crop simulators. \n  \nChristos Mitsanis\nPhD Student\, The University of Queensland\, ARC Centre of Excellence for Plant Success \nAgentic AI\, mechanistic networks and CGMs. \n  \nSophie (Qiaomin) Chen\nResearch Fellow\, The University of Queensland \nMulti-scale precision agriculture. Integrates crop modelling with machine learning. modelling of crop traits using simulation-generated data sets. \n  \nSebastian Lopez-Marcano\nSenior Manager Analytics\, The University of Queensland \nData analytics\, workflows. \n  \nJavier Fernandez\nResearch Fellow\, The University of Queensland \nCrop and agronomic modelling. \n  \nEric Dinglasan\nSenior Research Fellow\, Queensland Alliance for Agriculture and Food Innovation \nOptimisation strategies for QTL stacking models. Adapts methods proven in animal breeding to crops. \n  \n 
URL:https://www.plantsuccess.org/event/winter-school-in-ai-and-predictive-agriculture/
ORGANIZER;CN="Plant Success":MAILTO:admin@plantsuccess.org
END:VEVENT
END:VCALENDAR