Yujin K.

Ml Lidar Analytics @BNSF Railway

Engineered and developed a PointNet-based machine learning (ML) model for batch processing of large-scale LiDAR data in Azure, performing 3D analysis and volume calculations reducing processing time by 90%- Developed hydrology analysis solution using rasterized LiDAR data to identify flow accumulation regions for improved infrastructure longevity- Provisioned CPU systems for laser-equipped edge system, as well as contributed to edge computing initiatives- Designed deep learning model to classify 20 distinct obstruction types within LiDAR data