NYC Tree Map, 2025
NYC Tree Map, 2025
Touch Designer
Touch Designer
Created for Mediated Spaces a class taught by Jesse Stiles. This project takes the 2015 New York City Tree census as a database and passively explores it on the walls of the space. It sources images from a reference library of tree species to be displayed along with statistics from that exact street tree in New York. The display creates a
Exhibition
Theo Berry and Jesse Stiles
Bluecar LA Ridership Data, 2025
Bluecar LA Ridership Data, 2025
Python, ArcGIS, and Premiere Pro
Python, ArcGIS, and Premiere Pro
As an intern at the Commercial Rideshare Management team at the Los Angeles Department of Transportation I was tasked with making data standard and usable from over 8 years of the Bluecar service from 4 different providers. There were 11 different datasets with varying complications which were reduced to 3 with standard formatting and documentation. With it I created a report to be presented to LA city council including two animations.
Animation in After Effect for presentation, visualizing possible transition of retired Bluecar LA stations into mobility hubs
Machine Learning Dam Categorization, 2025
Machine Learning Dam Categorization, 2025
Python and ArcGIS
Python and ArcGIS
Using K-Clustering methods to categorize and assess US inventory of over 90,000 dams. K-Means clustering is a popular algorithm for grouping data points based on minimizing the distance to the center (centroid) of a cluster. This model uses a mixture of quantitative and categorical variables like dam height, age, water storage, drainage, state regulation, hazard potential and more. The categorization can be use improve analysis times when researched are limited for inspections, maintenance, and analysis. It can also just be used to repair datasets easier using averages from the cluster rather than the population.
This project was for the URP 402 Urban AI taught by Xiaofan Liang. See the full project here.
Perlin Noise-Field, 2025
Perlin Noise-Field, 2025
Touch Designer
Touch Designer
Project for Mediated Spaces with Jesse Stiles. This project uses projection mapping and particle simulation using Perlin 4D noise to create a wave formation around the space. The imagery is derived from particles moving with the noise pattern and is color mapped according to the age of the particle. The simulation is three dimensional and to capture the view there are six virtual cameras (mapped to the 6 projectors in the room) placed in the center of the generation.
The inspiration came from an interest in how different noise patterns are generated. Compared to true noise, Perlin noise tends to graduate between values giving it a more natural look, with higher dimensions having more subtle variations.
In blue cycle
Raw Output (Limited Resolution)
Noise-Field from afar