Rushan Wang

GI Geosciences Instrumentation and Data Systems

The 2025 Outstanding Student and PhD candidate Presentation (OSPP) Award is awarded to Rushan Wang for the poster/PICO entitled:

Advances in the Identification of Geological Discontinuities in Boreholes with Deep Learning (Wang, R.; Ziegler, M.; Volpi, M.; Manconi, A.)

Click here to download the poster/PICO file.

Rushan Wang is a PhD student at the WSL Institute for Snow and Avalanche Research SLF and ETH Zurich, supervised by PD Dr. Andrea Manconi, Dr. Michele Volpi, and Dr. Martin Ziegler. Her research focuses on developing machine learning methods to automatically detect and classify various discontinuities in typical geological datasets, with current work centered on data from the Mont Terri laboratory and plans to extend to other contexts.

At EGU25, she presented an efficient deep learning approach for identifying discontinuities in borehole images, highlighting the potential of such methods to improve rock mass characterization and monitoring of rock mass behavior.