Kenny Peng

Computer scientist working on algorithmic fairness in matching markets, lead author of Peng, Ryu, Kleinberg, Tardos & Garg's 2026 Nature Cities paper "Connecting application behavior to undermatching in New York City school choice" — the finding that Black, Hispanic, and low-income NYC applicants disproportionately undermatch to lower-quality programs than their lottery numbers would support, which directly motivates this vault's newest capture on recommendation-induced congestion. Matters here as a co-author with separate standing beyond that shared paper: he leads the undermatching study this congestion-mitigation paper builds on, and co-authored 2024's "Monoculture in Matching Markets" (NeurIPS) with entity-nikhil-garg.

References

• claim-recommendation-induced-congestion-erodes-offer-likelihood-guarantees · claim-balanced-capacitated-nudging-guarantees-safe-and-near-optimal-matches · claim-nyc-school-nudge-rct-significant-ranking-suggestive-matching-increase

• Capture: 10-inbox/raw/2026-10-07-outside-arxiv261008275-personalized-recommendations-without-inducing-congestion-mitigating.md

• 2026-10-14: the nudge RCT paper was confirmed accepted to ACM EC 2026 (SIGecom's flagship venue) under an unchanged author roster; its peer-reviewed camera-ready version restates the paper's figures, but no source independent of this author group has yet corroborated the deployment's zero-rejection result (claim-no-independent-source-corroborates-nyc-nudge-rct-zero-rejection-result).