I seek to leverage the power of data science, visualization, and web development
to lead better urban planning, public policy making, and business growth.
Currently a PhD student @ the Department of Urban Studies and Planning at MIT.
Skills used: R, Random Forest, XGBoost, Scenario Testing
Skills used: R, Multinomial Logistic Regression, App Wireframe, Profit Optimization
Skills used: Python, Web Scraping, Twitter API, Sentiment Analysis, Street Network Analysis (Pandana), Machine Learning (Scikit-learn), Data Visualization (Altair, HvPlot, Seaborn, Folium, Panel)
Skills used: Javascript, Leaflet, Billboard, HTML, CSS
Predict Philadelphia house values with spatial lag, spatial error and geographically weighted regression (GWR).
Skill used: Python, Machine Learning (Scikit-learn), K-Means, SVM, Deep Learning (Keras), Convolutional Neural Network (CNN), ResNet
Find the viable forest patches that are of
the most conservation importance through patch analyses. Skill used: Google Earth Engine