The ROSS Club hosts a talk by Dr. Jiating Li (University of Manitoba) on Thursday, October 15, 2026. Her lab combines satellites, drones, ground robots and field sensors with AI and physics-based models to predict crop performance. The talk shows how those observations become decisions in crop breeding and precision nutrient management.
About the speaker
Dr. Jiating Li is an Assistant Professor in the Department of Biosystems Engineering at the University of Manitoba, where she leads the Agricultural Intelligence and Digital Engineering (AIDE) Lab. Her research covers precision and digital agriculture, high-throughput plant phenotyping, agricultural automation and robotics, and physics-guided AI. She earned her PhD at the University of Nebraska-Lincoln (2023) and was a postdoctoral researcher at the University of Illinois Urbana-Champaign.
- Faculty page: Jiating Li, University of Manitoba
- Lab: AIDE Lab
The talk
From sensing to decisions through multi-scale observations and modeling for sustainable crop production
From the abstract:
Modern crop production is increasingly data rich, with observations available from satellites, drones, ground-based machinery or robots, and a growing range of environmental sensors. Yet transforming these observations into reliable and actionable knowledge remains a major challenge.
In this seminar, Dr. Jiating Li, Assistant Professor in the Department of Biosystems Engineering at the University of Manitoba, will introduce her research in advancing smart agriculture through digital technologies and artificial intelligence (AI). The presentation will highlight three interconnected research directions: (1) developing multi-scale sensing systems to capture plant traits across different spatial and temporal scales; (2) combining multimodal sensing data, AI, and physics-based models to improve the robustness of crop growth and yield prediction; and (3) translating sensing and modeling outputs into smarter decisions for applications such as crop breeding and precision nutrient management. Through examples from previous and ongoing research, the seminar will discuss not only what agricultural sensing systems can observe, but also how observations from different sensors and platforms can be integrated and converted into meaningful agricultural decisions. Ultimately, Dr. Li’s work aims to bridge engineering, crop science, and data analytics to develop intelligent agricultural systems that can sense, understand, and support better decisions in complex and changing environments.
When and where
- Date & time: Thursday, October 15, 2026, 11:00 am to 12:00 pm (Edmonton time)
- Location: MM Lab, UCOMM 4-140, University of Alberta
- Format: in person, with an online option
- Online: join via Zoom (meeting ID 997 5751 4008, passcode 306285)
- Add to calendar: Google Calendar or Apple / Outlook (.ics)
Registration and updates
Event registration (this event): Register through the Google Form →
Registration is highly encouraged, especially if you plan to attend in person: the MM Lab has limited seats, and the count helps us confirm the room.
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Questions in the meantime: xinyao1@ualberta.ca.