Tian Qiu

Cornell University

Papers

3

Total Citations

16

H-Index

2

About

Tian Qiu is an emerging researcher at the intersection of precision agriculture, remote sensing, and agricultural robotics, with a focus on developing cutting-edge computational and sensing solutions for modern horticultural challenges. Their work spans two complementary domains: hyperspectral disease monitoring in viticulture and 3D point cloud processing for robotic orchard management. Qiu's most-cited contribution applies hyperspectral sensing to non-destructively monitor foliar fungicide efficacy against grapevine powdery mildew, offering growers a data-driven tool to optimize spray intervals and combat the growing problem of fungicide resistance — a study that has already garnered 9 citations since 2023. In parallel, Qiu has made notable strides in robotic pruning, introducing the Real2Sim inverse framework to address incomplete point cloud data in apple orchard environments, accumulating 5 citations since 2024. Their most recent work tackles joint 3D segmentation across hierarchical orchard structures — from panels to individual branches — advancing the scalability of autonomous robotic operations. Though early in their career, Qiu's interdisciplinary contributions position them as a promising voice in smart agriculture, bridging plant health diagnostics with the robotics technologies reshaping the future of farming.

Research Focus

Key Achievements

2
H-Index
3
Papers
16
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Non-Destructive Monitoring of Foliar Fungicide Efficacy with Hyperspectral Sensing in Grapevine
9 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Cornell University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago