Resume

• Courses: Intro GIS, Geospatial Big Data Analytics, Spatial Databases, Cartography, Interactive Visualization

• Applied spatial analysis for large-scale land cover classification, processing 10TB+ per project of LiDAR, nDSM, and NAIP imagery, increasing geographic land cover data accuracy by 90% and accelerating decision-making.
• Trained and deployed Machine Learning AI-driven DCNN models for remote sensing image classification, improving classification accuracy by 25% and reducing processing time by 40%.
• Streamlined project pipeline and quality control, validation processes to reduce defects by 99%, enhance data consistency, and cut manual processing time by 50% through scripting automation with improved documentation.
• Led a team, delegating tasks and managing progress through continuous collaboration with clients and internal teams to ensure seamless execution across multiple initiatives.

• Analyzed coastal bluff erosion using remote sensing and ArcGIS tools, identifying high-risk areas and reducing projected erosion costs by 20% through data-driven control measures.
• Delivered FEMA floodplain Depth Grids with Python, JavaScript, and ESRI tools, enhancing flood risk evaluation, ensuring DFIRM data accuracy, and maintaining research integrity through rigorous validation and documentation.

• Optimized construction planning using advanced geospatial analysis, reducing project maintenance costs by 30% through improved road layout, utility mapping, and environmental assessments.
• Managed in-house GIS databases and quality control, ensuring 100% data accessibility, reducing inaccuracies, and improving project efficiency by 25% with data-driven reports in Power BI and Tableau.
• Administrated effective collaboration among engineering, operations, and project teams to maintain 100% accessibility of GIS data and maps, facilitating effective technical support towards informed decision-making with project managers.