Summary
Arslaan Khalid is a research scientist and coastal data scientist with nine years of experience building flood risk and real-time flood forecasting systems for estuaries and coastlines. He blends coastal and riverine engineering expertise—ADCIRC, Delft3D, HEC-RAS and FEMA mapping—with advanced data science skills in machine learning, computer vision, and big-data automation to extract flood-relevant features from satellite and street-level imagery. His work spans academic research and industry delivery, from developing high-resolution unstructured meshes and cloud-parallel hydrodynamic models to deploying citizen-science-enabled flood monitors for the Chesapeake Bay. Notably, he has applied semantic segmentation to infer building first-floor elevations and density for urban flood risk assessments, turning imagery into actionable hazard metrics. Based in the Washington DC–Baltimore area and currently at The Water Institute, he repeatedly combines novel modeling approaches with production automation to accelerate flood risk decision-making.
9 years of coding experience
4 years of employment as a software developer
Bachelor of Engineering (BE) Civil Engineering, Bachelor of Engineering (BE) Civil Engineering at National University of Sciences and Technology (NUST)
Doctor of Philosophy - PhD Civil Engineering - Water Reources Engineering, Doctor of Philosophy - PhD Civil Engineering - Water Reources Engineering at George Mason University