Portfolio

Data Analysis and Predictive Modeling

I conducted multiple data analysis projects by using R and Python, and focused on interpreting, engineering data and building models with the principles of machine learning. My projects response to the solutions for real-world concerns in resource allocation.

Bike share space-time prediction, Philadelphia

The algorithm model aims to predict Indego bike share demand in Philadelphia by taking time, physical and socio-economic factors into account. The model can assist Indego to better allocate bike resources based on demand varying across time and space.

EMS call prediction, Virginia Beach

With existing EMS call records data, this project predicted space and time distribution of future EMS calls by adopting Poisson Regression and Linear Regression, and an APP wireframe was also developed for ambulance drivers by providing the fastest route to direct to the right place based on modeling results.

Retail theft risk prediction, Chicago

This project predicts retail theft risk in Chicago based on crime records and various risk factors, and also figures out potential risk hotspots.

Larcerny index prediction, San Francisco

The Python project predicts larcerny risk in San Francisco by using “larceny index” as the dependent variable. It includes a variety of interactive visuals for exploratory analysis and modeling.

Spatial Analysis

I equipped myself with ArcGIS to conduct spatial analysis for different topics in city and regional planning.

TOD analysis in Philadelphia

Evaluated the feasibility of TOD along SEPTA metro lines in Philadelphia

Urban Growth Boundary in Lancaster County

Explored the effects of Urban Growth Boundary on building densities and land use

Urban Growth VS. Development Suitability

Analyzed the environmental sensitivity of land in Pennsylavnia to assess furture development through raster overlays

Smart City Project

As a student in Smart Cities concentration, I did a project in improving intersection safety by programming with Arduino for a working prototype. The project is called “SMARTISS-Smart Intersection Safety System”. In brief, the system engages various sensors to detect pedestrains who are crossing the intersection when the traffic light is red, and will remind drivers that are coming towards the intersection.