Transforming transportation data into actionable insights that drive decision-making for transit agencies and government clients. Specializing in travel demand modeling, trend analysis, and accessibility studies, leveraging big data to support projects such as network redesigns, congestion management, and equity analysis. Delivering high-quality data products, predictive models, and interactive dashboards to enhance public mobility and optimize transportation systems across regions.

-Extracted core demands of users in the scene investigation of the rest area, persuaded opponents by ROI data support and a clear functional framework, and make product take the lead in China's navigation application market.-Patented the product which developed the model recommending the fastest lane at toll station scenario and transformed from planar elements to 3D models. This product feature has been used over 1,000,000 times until now.-Communicated with teams, followed up demands, made schedules and undertook other project management responsibilities. Accomplished tasks include toll station model, 3D pier display and translucent tunnel display effect.

-Collected POI data by pulling data from SQL database, cleaned and wrangled data by Python, visualized data and made storytelling with respect to the relationship between Shanghai house pricing and transportation development with Excel and Datamap. -Proposed new indexes to predict the trend of rental prices, such as focusing on the number of high-paying jobs in the area.

-Involved in the project of "Report on China's Urban Logistics Competitiveness (2020)", responsible for data analysis using PCA model, result visualization on GIS, document compilation, etc. The final results include ranking list of China's urban logistics competitiveness, case analysis of typical cities, etc., attracting broad attention of the provincial governments.