about me


Hey there! I am Jack Rummler - a Florida born, Philadelphia residing lover of all things urban and spatial. I currently work as a policy and data analyst at the Defender Association of Philadelphia and a geospatial data contractor for the World Bank's Urban Resilience unit.


My interests lie in using spatial data and urban policy to build communities and spaces that are socially and ecologically resilient.


Click my links below to check out my socials, and keep scrolling for some of my spatial analytics, public policy, and writing works. Thanks for stopping by!


data analytics

FORECASTING BUS TRANSIT ALTERNATIVES IN EL PASO


Building a latent bus transit demand model and informational evaluative app to allow Sun Metro transit planners to build more equitable and profit maximizing routes.


Skills used: R, Random Forest, XG Boost, Google Cloud Services


Project Team: Charlie Huemmler, Yingxue Ou, and Jack Rummler


Final Presentation


R Markdown


Web App

DETECING HURRICANE DAMAGE USING REMOTE SENSING AND MACHINE LEARNING


Using deep learning models to classify hurricane damage from post-Hurricane Harvey satellite imagery.


Skills used: Python, convolutional neural networks, VGG-16, residual neural networks


Project Team: Ben Keel, Jack Rummler, and Kate Tanabe


Presentation


Report


Jupyter Notebook

URBAN GROWTH MODELING IN THE NASHVILLE MSA


Forecasting demand and supply side urban development using binary logistic regression.


Skills used: R, binary logistic regression, policy communication


Project Team: Jack Rummler and Shengqian Wang


R Markdown


Policy Poster

CLASSIFYING EUROSAT LAND COVER DATA


Developing several convolutional neural network models to predict 10 different land cover classifications, with an accuracy of nearly 80%.


Skills used: Keras, Tensorflow, convolutional neural networks


Jupyter Notebook

PREDICTING NEW JERSEY TRANSIT TRAIN DELAYS


Accurately predicted train delays on the Northeast Corridor two hours in advance with an average error of only 26 seconds.


Skills used: R, OLS regression, binary logistic regression


Project Team: Rebekah Adams and Jack Rummler


R Markdown


YouTube Video

HOME PRICE MODELING IN PHILADELPHIA, PA

Using a Random Forest Regression to predict home prices with 75% accuracy.


Skills used: Python, Random forest regression


Jupyter Notebook

writing

EVALUATION OF EAST GAINESVILLE'S MICROTRANSIT


A study of Gainesville, Florida's microtransit pilot and a recommendation guideline for the effectiveness and stability of micromobility services.


Skills used: Literature and practice review, technical memorandums, transit planning


Project Team: Dr. Ruth Steiner, Dr. Siva Srinivasan, Dr. Mehri Mohebbi, Dr. Xiang Yan, Sagar Patni, Larissa Krinos, Juan Suarez, Jack Rummler


Final Report

RESILIENCY FOR A BETTER DUVAL: SENIOR CAPSTONE


A scoping literature review and case study analysis of best practices in urban resilience planning to inform recommendations for Jacksonville, Florida. Mentored by Dr. Azza Kamal.


Skills used: Social sciences and qualitative research, social-ecological resilience practice


Final Report

REGRESSION METHODS TO ASSESS PHILADELPHIA'S BLOCK GROUP INCOME


Using spatial statistics and different regression methods to investigate relationship between census block level median household income and neighborhood characteristics.


Skills used: R, ArcGIS Pro, GeoDa, spatial lag, spatial error, geographic weighted regression


Project Team: Haobing Liu, Jack Rummler, and Kate Tanabe


Final Report