1) Reading the Streets: What Citi Bike Data Reveals About Our Cities // Patrick ClearyDive into publicly available Citi Bike trip data to discover where New Yorkers are traveling by bike. This talk will center around an interactive website that displays Citi Bike trips. We will discuss how it was built and ways it can be used to find insight into bike travel. See how new bike infrastructure such as the First Avenue Tunnel or expanded Queensboro bridge bike path has impacted this method of transportation.
2) Bike-Track: A Manhattan Citibike Custom Live Tracker PCB Board // David Kaplan, James Ryan, Vaibhav Hariani, and Kristof Jablonowski
This presentation by a group of designers and engineers maps every Citi Bike station in Manhattan to a unique RGB LED on a custom PCB Board (~650 LEDs). This board was created for a Data Visualization course at Cooper Union.
At the moment, the board has 3 main modes that can be cycled through via a companion app that we developed.
The primary view renders real-time information about every dock and station in the city. Brightness corresponds to the number of bikes (or docks available), and color represents station status (red for no bikes, blue for regular bikes, green for >25% ebikes).
The audience will participate by interacting with the app and observing the PCB board.
3) Visualizing Citi Bike Data as a Strava-style Heatmap // Danny Yang
In this lightning talk, I’ll share how I built a Strava-style heatmap using my own Citi Bike ride history.
The project started as a personal data-viz experiment: exporting my ride records, estimating likely routes between stations with the Google Maps API, and rendering them as a heatmap. I’ll briefly cover the data processing, key design choices, and what worked (and didn’t) when turning sparse trip data into something that looks and feels like a GPS-based activity map.
The full write-up and code are available here:
https://yangdanny97.github.io/blog/2026/01/17/citibike-strava-heatmapThis session is for people interested in data visualization, geospatial data, or small “data about me” projects. Attendees will spend the time seeing a quick walkthrough of the approach, example visuals, and practical lessons they can reuse in their own projects.
4) Where Tickets Happen: A High-Resolution Geospatial Study of Parking Enforcement in New York City // Michael ForsterWhat started with a query into a couple of parking tickets led Michael Forster down a rabbit hole of publicly available ticket data. What he thought would be a quick afternoon with a spreadsheet and a few scripts became a year-long exploration into data engineering, resulting in a database of over 90 million parking tickets issued across 10 years.
This lightning talk follows that journey and how he used tools like Postgres, Kafka, and ClickHouse to build a pipeline to ingest, process, and analyze the data, plus the long road to geocoding nearly every ticket in NYC.
