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Add as preferred source Many New York City eighth-graders—particularly those from underserved communities—aren't applying to academically competitive high schools where they could succeed, according to new Cornell research.
In partnership with New York City Public Schools (NYCPS), the research team is putting its findings into practice to help combat the phenomenon, known as "undermatching."
New York City's public high school application process is one of the nation's largest and most complex, requiring more than 60,000 eighth-graders to navigate hundreds of options. The system is designed to give students access to schools across the city, regardless of their neighborhood—but that level of choice can quickly become overwhelming, the researchers said.
"It's a crazy complex process for how students apply and then match with high schools in New York City," said Nikhil Garg, assistant professor of operations research and information engineering at Cornell Tech and the Cornell Duffield College of Engineering and a co-author of the paper, "Connecting application behavior to undermatching in New York City school choice," published in Nature Cities . "With that flexibility and equality of access comes the challenge of figuring out how to navigate 900 options and decide which ones to apply to."
The research was led by Cornell Tech doctoral students Kenny Peng and Emily Ryu and was also co-authored by Jon Kleinberg, the Tisch University Professor of Computer Science and Information Science, and Eva Tardos, the Jacob Gould Schurman Professor of Computer Science, both in Cornell Bowers Computing and Information Science.
The researchers analyzed data from nearly 59,000 students who participated in New York City's high school admissions process during the 2022–23 school year. They looked not only at where students were admitted, but where they could have been admitted had they applied to different schools. By combining admissions data with a model of how students choose schools under uncertainty, the team assessed whether students could have applied to higher-performing programs and where their application behavior may have limited their options.
"Intuitively, we knew that the complexity of the system was a challenge for students and families," Peng said. "But to address this challenge, we thought it was important to first carefully quantify that effect on real data."
The researchers found that, on average, New York City students enrolled in schools that admitted about 64% of applicants, even though they could have been admitted to schools that admitted only about 37% of applicants, suggesting many students were not applying to the most competitive schools within reach.
This gap was highest for students with the most competitive applications and for Black, Hispanic and lower-income applicants—a finding that raised questions about whether the complexity of the application process itself was driving inequities in student behavior and outcomes, the researchers said. The study indicates that providing students with more personalized guidance on where they have a realistic chance of admission could help reduce inequities in the admissions process.
A second paper examines how personalized recommendation systems can help students navigate the high school admissions process. Led by doctoral student Erica Chiang, who partnered with NYCPS as a Siegal PiTech Ph.D. Impact Fellow at Cornell Tech, the new system developed by researchers and deployed by NYCPS delivered personalized email recommendations to applicants during the 2025–26 admissions cycle. The paper won the Best Paper with Student Lead Author Award at the ACM Conference on Economics and Computation on July 7.
"The goal is to recommend lists of schools that students should consider applying to in order to make the process easier," Garg said.
Messages were sent to students attending middle schools that historically sent relatively few students to high-performing high schools and highlighted nearby programs where students had a strong predicted chance of admission. In a randomized controlled trial, students who received the recommendations were 59% more likely to apply to a recommended program than students who did not receive them, suggesting that personalized guidance can help students discover and consider schools they might otherwise overlook.
"We worked very closely with NYCPS to understand the complexities of the admissions system and the challenges students face in the application process," Chiang said. "The collaboration helped us understand what would be most useful for students, along with the potential consequences and technical constraints of delivering recommendations in practice."
Providing recommendations in a capacity-constrained admissions system presents unique challenges, the researchers found. "Since each school has a limited number of seats, one student's choices can affect outcomes for others," Chiang said. "Recommending the same school to too many students could make the school more competitive than students were led to expect, and that could harm students or decrease trust in the match process."
The team also said that preserving student choice was a central design principle.
"We hope to increase access to high-performing schools, but our goal is not to tell students where they should apply," Chiang said. "We just want to give them more information about schools they may not have known about, to support them in making informed choices while still respecting their preferences."
Ultimately, Garg said success will be measured by whether the system helps the city deliver on its promise of equitable access. "The vision is to close the gap between the goals of the system and the on-the-ground...
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