Geng Wang

Geng Wang is a Ph.D. candidate in Smart Forestry at Beijing Forestry University (China). He is currently a Visiting Ph.D. Student at the Forest Damage Centre, Swedish University of Agricultural Sciences (SLU). His visiting research period spans from November 2025 to November 2026.

Geng’s research focuses on the intersection of forest protection and advanced remote sensing technologies. He specializes in applying deep learning, machine learning, and statistical algorithms to monitor forest health.

Geng's research has been supported by the National Natural Science Foundation of China (NSFC) and the National Key Research and Development Program of China. He specializes in multi-modal data fusion (LiDAR, Hyperspectral, and Optical data) and has developed novel instance segmentation networks to identify individual trees at different infection stages. His work aims to overcome the challenges of detecting early-stage forest stress and scattered outbreaks in complex forest environments.