Nikhil Garg

Computer scientist at Cornell Tech who runs the "Garg Lab," working on recommender systems and algorithmic decision-making inside real, capacity-constrained matching markets rather than in the abstract. Matters to this vault as the recurring corresponding-author anchor of a small cluster of connected papers it is now tracking: this capture's 2026 deployment paper on recommendation-induced congestion in the NYC high school match, the directly motivating 2026 Nature Cities undermatching study, and 2024's "Monoculture in Matching Markets" (NeurIPS) — three distinct venues, the same underlying research program on what happens when algorithms sit on top of scarce, shared allocations.

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).