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1. Analyzed regional crash data using Python, SQL, and Excel to identify high-risk patterns and support safety interventions.
2. Created interactive geospatial visualizations with QGIS and ArcGIS to highlight demographic and crash trends.
3. Supported Travel Demand Model calibration using Cube to enhance transportation planning and future scenario analysis.
4. Delivered public-facing reports and dashboards to translate technical findings into accessible insights for stakeholders.
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1. Developed a Python model to integrate ACSM and H-TDMA data, improving atmospheric particle representation.
2. Implemented differentiable aerosol microphysics in Julia to refine cloud-aerosol interaction modeling.
3. Designed flood-resilient drainage systems using HEC-HMS and HEC-RAS based on historical precipitation analysis.
4. Balanced environmental and financial impacts through cost-benefit analyses on large-scale infrastructure projects.
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1. Built ML models (regression, PCA, neural networks) to predict traffic volume using weather and road characteristics.
2. Optimized Chicago transit routes with custom Python algorithms to minimize passenger travel time and cost.
3. Applied R and simulation tools to teach risk analysis and stochastic modeling in civil engineering contexts.
4. Proficient in Python, R, SQL, MATLAB, Java, and Julia, with fluency across Civil 3D, MicroStation, and ArcGIS platforms.
