SEC scholar 1 August – 30 September 2026
Dr. Zuoya Liu is currently a Senior Research Scientist at the Finnish Geospatial Research Institute (FGI) in the National Land Survey of Finland (https://www.maanmittauslaitos.fi), and an Academy Research Fellow of Finland, RCF, starting from September 1, 2025. He comes from a world-leading university, remote sensing in Wuhan University has been ranked #1 in the Academic Ranking of World Universities since 2017, where he completed mhis PhD in Geodesy and Survey Engineering.
He came to FGI in 2022. FGI has been ranked #1 in Laser Scanning, Photogrammetry and UAV by ScholarGPS. The persons he collaborates with in FGI, have been PIs for two Research Council flagships, one Strategic Research Council project and one Center of Excellence, and 15+ international science projects. His research lies at Localization and Navigation Technologies Indoors and Outdoors – with a special focus on Precision Forestry and Intelligent Systems.
Liu’s research interests include UWB, Acoustic, IMU, Laser Scanning, Sensor Fusion, Internet-of-Things, Field Surveying, and Mini-Drones. He also have more than six years of experience in the industry, acting as a HW, SW or System Engineer, full-time or part-time at Hi-cloud, ZLNavi and Field. He contributes to the industry all the time. (https://zyliu0017.github.io/)
During the residency, Dr. Zuoya will collaborate with Professor Milan Horemuz and Associate Professor Jingbin Liu on the project: “Efficient and Accurate Tree Localization Using Ultra-Wideband Under a Forest Canopy for Precision Forestry”. The project will explore how the latest ultra-wideband ( UWB) technology can be used to measure tree positions efficiently and accurately in different boreal forest environments.
The aim of the visit is to combine Dr. Zuoya’s expertise and experience in localization technologies with Professor Milan’s expertise in land surveying and Professor Jingbing Liu’s expertise in spatial data processing. Together, they will explore how spatiotemporal data processing and AI methods can be applied to UWB localization to improve the accuracy of tree-position measurements under varying forest environments and enhance system robustness, as well as to investigate other potential industrial applications.
Contact: zyliu0017@gmail.com
