Alireza Pourbahramian

WORK HISTORY

EDUCATION

ABOUT ALIREZA POURBAHRAMIAN

I am a geospatial data engineer focused on building scalable, production-grade LiDAR analytics systems for complex rail and infrastructure environments. My work spans the full spatial data lifecycle—from raw multi-session point-cloud integration to feature-level decision modeling and vectorized 3D deliverables—where accuracy, performance, and traceability are critical.At Lux Modus, I design and optimize end-to-end LiDAR processing pipelines using Python and cloud-native architectures, integrating large LAS datasets, automating 3D feature extraction, and implementing robust alignment, clustering, and classification logic. Rather than treating machine learning as a black box, I emphasize data-centric design, engineered spatial features, and failure-aware workflows that remain reliable across varying point densities and acquisition conditions.With a strong foundation in geometric computation, spatial databases, and applied machine learning, I approach LiDAR automation as a systems engineering problem—not just a modeling task. My focus is on building modular, interpretable, and high-performance spatial data pipelines that scale confidently from analysis to production and support defensible, real-world decision-making.