Master of Urban Spatial Analytics
Master of Landscape Architecture
University of Pennsylvania
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Skill used: Python, Random Forest, K-means Clustering, Data Visualization (Altair, HvPlot, Seaborn)
This project aims to use New York City as a case, study how the pandemic influenced the Airbnb market in different aspects, and provide advice for both Airbnb hosts and guests in the post-pandemic future.
Skill used: R, ArcGIS, Logistic Regression
With climate change, more and more big fires are happening in northern California. We plan to develop a wildfire prediction model from an ecological perspective by considering natural and human factors in our model and proposing a forest management system of prescribed fire. This study is to build a logistic model for a fire management App, “SmartBurn.”
App introduction
Data repository
Skill used: R, OLS Modeling, Spatial Lag
As Zillow has realized that its housing market predictions are not as accurate as they could be because they do not factor in enough local intelligence in Mecklenburg, this project is to improve Zillow’s housing market predictions for Mecklenburg.
Skill used: R, Linear Regressions
One of urban bike share systems’ most challenging operational problems is the need to re-balance bicycles across the network. Re-balancing is to predict bike share demand for all docks at all times and redistribute bikes to ensure a bike or a docking place is available when needed. In this study, modeling and validation with accounting for weather and time effects and experimenting with some amenity features will give us a window into how we can use time-space predictive modeling to address an operations issue.
Skill used: R, Poisson Regression
Skill used: ArcGIS, Rhino, Grasshopper, After Effect
Seeking reforestation opportunities to reduce air pollution at Pittsburgh, PA
Skill used: ArcGIS, ArcPy
Explore relationship between urban green space and health with ArcPy
Skill used: Python, sentiment analysis