Alex Chohlas-Wood

@alexchohlaswood.com

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Assistant professor at NYU interested in computational public policy and the criminal justice system. Co-direct @comppolicylab.bsky.social.📍NYC 🏳️‍🌈 alexchohlaswood.com

A 911 call dispatcher working in front of five open screens. CC By 2.0. Source: https://www.flickr.com/photos/143513894@N04/27188584211
A time series of overnight subway patrols between September 2019–June 2025. Subway patrols more than doubled after the NYPD's policy announcement, from about 7,500 train patrol calls per month before the announcement to over 15,000 calls per month after the announcement.
A screenshot of NYC's Open Data portal listing NYPD's "Calls for Service (Historic)" dataset, with nearly 50 million rows.
Police officers face away from the camera toward a New York City subway train. The photo is taken through a fare gate. Photo credit: Metropolitan Transit Authority via CC 2.0.
A hand holding a smartphone displaying a court date reminder on screen.
Two students collaborating on a plot on a whiteboard.
A chart of regret vs. iteration. Random assignment methods accumulate a lot of regret over the course of an experiment, whereas bandit methods like UCB and Thompson sampling accumulate minimal regret.
A Pareto curve, showing the tradeoff between helping people get to court and the proportion of people in a target group who get the benefit of rides. The chart also shows a slider bar indicating a survey response, with the selection corresponding to the point of maximum utility.
A Pareto curve, showing the tradeoff between helping people get to court and the proportion of people in a target group who get the benefit of rides. The chart also includes a vertical line indicating demographic parity, which is not at the same point as maximum utility.
The graphic we showed survey respondents. There are five options presented, with various amounts of average spending per Black and White person. Each option also has an associated number of people who avoid jail, with the highest number associated with more spending per White person than Black person.
A Pareto curve, showing the tradeoff between helping people get to court and the proportion of people in a target group who get the benefit of rides. Also shown is an "increasing preference" line pointing up and to the right, and a point at the intersection of the line and the curve indicating maximum utility.
A Pareto curve, showing the tradeoff between helping people get to court and the proportion of people in a target group who get the benefit of rides.
A map of the Boston area, showing residents in different colors by their race/ethnicity. A star is in the center of the map surrounded by a circle; most of the people in the circle are white residents, with some Asian and some Hispanic residents as well. A large population of Black and Hispanic residents sits south of the city center and is outside of the circle.
An image of two women appearing to shake hands outside of a car.
A screenshot of the first page of our paper, Learning to Be Fair, showing the title and abstract.
This shows a snippet of R code that says "beepr::beep(8)".
A hand holding a smartphone displaying the reminders on screen.
A diagram of the different messages that people may receive to remind them of upcoming court dates.