See also Google Scholar See homepage for representative papers. "Lean" links refer to a Lean formalization of the paper's mathematical statements, using the EconCSLib project.

Working Papers

  1. W8
    The Forest from the Trees: Lessons on Public-Sector Deployment from an Academic Collaboration with NYC Department of Parks and Recreation
    Erica Chiang, Katelyn Liu, Anum Ahmad, Zhi Liu, Gabriel Agostini, Tyler Gibson, Uma Bhandaram, and Nikhil Garg
  2. W7
    What’s Wrong With Surveillance Pricing?
    Travis Lloyd, Nikhil Garg, Karen Levy, and Daniel Susser
    California Law Review, 2027 (Pending official Editorial Board selection)
  3. W6
    Paper Skygest: Personalized Academic Recommendations on Bluesky
    arxivcode
    Sophie Greenwood and Nikhil Garg
    Presented as talk at IC2S2‘26
  4. W5
    Redesigning Service Level Agreements: Equity and Efficiency in City Government Operations
    arxivcode
    Zhi Liu and Nikhil Garg
    Major revision at Manufacturing & Service Operations Management (M&SOM) Conference version published at ACM Conference on Economics and Computation (EC‘24)
  5. W4
    Hitting a Moving Target: Test-Time Adaptation for AI Text Detection under Continual Distribution Shift
    arxivcode
    Kevin Ren, Manish Raghavan, and Nikhil Garg
  6. W3
    EconCSLib: AI-Assisted Lean Formalization for Economics & Computation Research
    Nikhil Garg
    Presented at EC‘26 Workshop on AI-Driven Research in EconCS (AI-EconCS‘26)
  7. W2
    The Subjectivity of Monoculture
    arxiv
    Nathanael Jo, Nikhil Garg, and Manish Raghavan
  8. W1
    Optimal Strategies in Ranked-Choice Voting
    arxivcode
    Sanyukta Deshpande, Nikhil Garg, and Sheldon Jacobson

Journal Articles

  1. 2026 J15
    Connecting Application Behavior to Undermatching in New York City School Choice
    Nature Cities, Accepted
    Kenny Peng, Emily Ryu, Jon Kleinberg, Eva Tardos, and Nikhil Garg
  2. 2026 J14
    Combating Gerrymandering with Ranked Choice Voting: An Experimental Analysis of Multimember Districts in the United States
    Operations Research
    Nikhil Garg, Wes Gurnee, David Rothschild, and David B. Shmoys
    Conference version published in ACM Conference on Economics and Computation (EC‘22) Cornell Chronicle, San Francisco Chronicle.
  3. 2026 J13
    Dropping Standardized Testing for Admissions Trades Off Information and Access
    Management Science
    Nikhil Garg, Hannah Li, and Faidra Monachou
    Conference version published in ACM Conference on Fairness, Accountability, and Transparency (FAccT‘21); also appeared in EAAMO‘21 and in the 2021 NBER Decentralization Conference ACM EAAMO Student Paper Award, 2021 INFORMS DEI Best Student Paper Award, 2022 Yale Insights.
  4. 2026 J12
    Improving flood detection with large-scale dashboard camera data
    Nature Communications
    Matt Franchi, Nikhil Garg, Wendy Ju, and Emma Pierson
  5. 2026 J11
    Simpler Than You Think: The Practical Dynamics of Ranked Choice Voting
    Journal of Computational Social Science
    Sanyukta Deshpande, Nikhil Garg, and Sheldon Jacobson
  6. 2025 J10
    Inferring fine-grained migration patterns across the United States
    Nature Communications
    Gabriel Agostini, Rachel Young, Maria Fitzpatrick, Nikhil Garg, and Emma Pierson
    Association of American Geographers Best Student Paper Award, 2026 (Awardee: Gabriel Agostini) IPUMS Spatial Student Research Award, 2026 (Awardee: Gabriel Agostini) Cornell Chronicle.
  7. 2025 J9
    "Shopping Around": An Experiment in Preferences and Incentives for Placing Long-term Patients
    Proceedings of the ACM on Human-Computer Interaction
    Vince Bartle, Nicola Dell, and Nikhil Garg
    Journal Track for 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW‘25) Impact Recognition at CSCW ‘25 Cornell Chronicle.
  8. 2025 I1
    Heterogeneous participation and allocation skews: when is choice “worth it”?
    ACM SIGecom Exchanges
    Nikhil Garg
    Invited; lightly reviewed by editors
  9. 2025 J8
    Faster Information for Effective Long-Term Discharge: A Field Study in Adult Foster Care
    Proceedings of the ACM on Human-Computer Interaction
    Vince Bartle, Ashley Shearer, Alexandra Wroe, Nicola Dell, and Nikhil Garg
    Journal Track for 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW‘25). Also appeared in EAAMO‘23 Best Paper Award, and Diversity & Inclusion Recognition at CSCW ‘25 Cornell Chronicle.
  10. 2025 J7
    Addressing Discretization-Induced Bias in Demographic Prediction
    PNAS Nexus
    Evan Dong, Aaron Schein, Yixin Wang, and Nikhil Garg
    Conference version appeared in ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT 2024).
  11. 2023 J6
    Quantifying Spatial Under-reporting Disparities in Resident Crowdsourcing
    Nature Computational Science
    Zhi Liu, Uma Bhandaram, and Nikhil Garg
    Conference version published in ACM Conference on Economics and Computation (EC‘22), titled “Equity in Resident Crowdsourcing: Measuring Under-reporting without Ground Truth Data” INFORMS Junior Faculty Interest Group Paper Award (Finalist), 2023 Cornell Chronicle.
  12. 2022 J5
    Driver Surge Pricing
    Management Science
    Nikhil Garg and Hamid Nazerzadeh
    Conference version published in EC‘20.
  13. 2021 J4
    Designing Informative Rating Systems: Evidence from an Online Labor Market
    Manufacturing & Service Operations Management
    Nikhil Garg and Ramesh Johari
    New York Times, Stanford Engineering magazine. M&SOM student paper award (2nd place), 2020 Conference version published in EC‘20.
  14. 2020 J3
    Markets for Public Decision-making
    Social Choice and Welfare
    Nikhil Garg, Ashish Goel, and Benjamin Plaut
    Conference version published in WINE‘18.
  15. 2019 J2
    Iterative Local Voting for Collective Decision-making in Continuous Spaces
    Journal of Artificial Intelligence Research (JAIR)
    Nikhil Garg, Vijay Kamble, Ashish Goel, David Marn, and Kamesh Munagala
    Conference version published in WWW‘17.
  16. 2018 J1
    Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes
    Proceedings of the National Academy of Sciences (PNAS)
    Nikhil Garg, Londa Schiebinger, Dan Jurafsky, and James Zou

Peer Reviewed Conference Proceedings (without journal versions)

  1. 2026 C34
    Measuring the Impact of Urban Cycling Infrastructure with Large Scale E-Bike GPS Data
    EAAMO‘26
    Gabriel Agostini, Nikhil Garg, and Emma Pierson
    Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO‘26)
  2. 2026 C33
    Personalized Recommendations without Inducing Congestion: Mitigating Disparities in the NYC High School Match
    EC‘26
    Erica Chiang, Kenny Peng, Rebecca Lichtenstein, Brielle McDaniel, Kristen O’Neil, Dejaunique Thomas, Lianna Wright, Jon Kleinberg, Eva Tardos, and Nikhil Garg
    ACM Conference on Economics and Computation (EC‘26)
    EC Best Paper with Student Lead Author, 2026 (2 awards out of 1,111 submissions) INFORMS Doing Good with Good OR Student Paper Award, 2026 (Finalist; winners TBA) Plenary talk at IC2S2‘26 (top 2.3% of submissions)
  3. 2026 C32
    Position: Use Sparse Autoencoders to Discover Unknowns
    ICML‘26 Position Paper Track
    Kenny Peng, Rajiv Movva, Jon Kleinberg, Emma Pierson, and Nikhil Garg
    International Conference on Machine Learning (ICML‘26 Position Paper Track)
  4. 2026 C31
    How Many Features Can a Language Model Store Under the Linear Representation Hypothesis?
    COLT‘26
    Nikhil Garg, Jon Kleinberg, and Kenny Peng
    Conference on Learning Theory (COLT‘26)
    Spotlight Talk at ICML Workshop on Compositional Learning (3 of 210 submissions)
  5. 2026 C30
    Urban Incident Prediction with Graph Neural Networks: Integrating Government Ratings and Crowdsourced Reports
    AAAI‘26
    Sidhika Balachandar, Shuvom Sadhuka, Bonnie Berger, Emma Pierson, and Nikhil Garg
    AAAI Conference on Artificial Intelligence (AAAI‘26)
  6. 2026 C29
    Capacity Constraints Make Admissions Processes Less Predictable
    AAAI‘26
    Evan Dong, Nikhil Garg, and Sarah Dean
    AAAI Conference on Artificial Intelligence (AAAI‘26)
    Oral presentation.
  7. 2025 C28
    Correlated Errors in Large Language Models
    ICML‘25
    Elliot Myunghoon Kim, Avi Garg, Kenny Peng, and Nikhil Garg
    International Conference on Machine Learning (ICML‘25)
  8. 2025 C27
    Sparse Autoencoders for Hypothesis Generation
    ICML‘25
    Rajiv Movva, Kenny Peng, Nikhil Garg, Jon Kleinberg, and Emma Pierson
    International Conference on Machine Learning (ICML‘25)
  9. 2025 C26
    Learning Disease Progression Models That Capture Health Disparities
    CHIL ‘25
    Erica Chiang, Divya M Shanmugam, Ashley Beecy, Gabriel Sayer, Deborah Estrin, Nikhil Garg, and Emma Pierson
    Conference on Health, Inference, and Learning (CHIL ‘25)
    Best Paper Award for Impact & Society at CHIL ‘25
  10. 2025 C25
    Balancing Producer Fairness and Efficiency via Prior-Weighted Rating System Design
    ICWSM ‘25
    Thomas Ma, Michael S. Bernstein, Ramesh Johari, and Nikhil Garg
    International AAAI Conference on Web and Social Media (ICWSM ‘25)
  11. 2025 C24
    A No Free Lunch Theorem for Human-AI Collaboration
    AAAI‘25
    Kenny Peng, Nikhil Garg, and Jon Kleinberg
    AAAI Conference on Artificial Intelligence (AAAI‘25)
  12. 2024 C23
    Monoculture in Matching Markets
    NeurIPS ‘24
    Kenny Peng and Nikhil Garg
    Neural Information Processing Systems (NeurIPS ‘24)
  13. 2024 C22
    User-item fairness tradeoffs in recommendations
    NeurIPS ‘24
    Sophie Greenwood, Sudalakshmee Chiniah, and Nikhil Garg
    Neural Information Processing Systems (NeurIPS ‘24)
  14. 2024 C21
    Ending Affirmative Action Harms Diversity Without Improving Academic Merit
    EAAMO ’24
    Jinsook Lee, Emma Harvey, Joyce Zhou, Nikhil Garg, Thorsten Joachims, and René F. Kizilcec
    Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO ’24)
  15. 2024 C20
    Wisdom and Foolishness of Noisy Matching Markets
    arxiv
    EC‘24
    Kenny Peng and Nikhil Garg
    ACM Conference on Economics and Computation (EC‘24)
  16. 2024 C19
    Equitable Congestion Pricing under the Markovian Traffic Model: An Application to Bogota
    arxiv
    EC‘24
    Alfredo Torrico, Natthawut Boonsiriphatthanajaroen, Nikhil Garg, Andrea Lodi, and Hugo Mainguy
    ACM Conference on Economics and Computation (EC‘24)
  17. 2024 C18
    Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers
    NAACL‘24
    Rajiv Movva, Sidhika Balachandar, Kenny Peng, Gabriel Agostini, Nikhil Garg, and Emma Pierson
    The North American Chapter of the Association for Computational Linguistics (NAACL‘24)
  18. 2024 C17
    Domain constraints improve risk prediction when outcome data is missing
    ICLR‘24
    Sidhika Balachandar, Nikhil Garg, and Emma Pierson
    International Conference on Learning Representations (ICLR‘24)
  19. 2024 C16
    Reconciling the accuracy-diversity trade-off in recommendations
    WWW‘24
    Kenny Peng, Manish Raghavan, Emma Pierson, Jon Kleinberg, and Nikhil Garg
    The ACM Web Conference (WWW‘24)
    Oral Presentation
  20. 2024 C15
    A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing
    AAAI‘24
    Gabriel Agostini, Emma Pierson, and Nikhil Garg
    AAAI Conference on Artificial Intelligence (AAAI‘24)
    Oral Presentation
  21. 2024 C14
    Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling
    AAAI‘24
    Zhi Liu, Sarah Rankin, and Nikhil Garg
    AAAI Conference on Artificial Intelligence (AAAI‘24)
  22. 2023 C13
    Supply-Side Equilibria in Recommender Systems
    NeurIPS ‘23
    Meena Jagadeesan, Nikhil Garg, and Jacob Steinhardt
    Neural Information Processing Systems (NeurIPS ‘23)
  23. 2023 C12
    Interface Design to Mitigate Inflation in Recommender Systems
    RecSys ’23 Short paper
    Rana Shahout, Yehonatan Peisakhovsky, Sasha Stoikov, and Nikhil Garg
    ACM Conference on Recommender Systems (RecSys ’23 Short paper)
  24. 2023 C11
    Coarse race data conceals disparities in clinical risk score performance
    ML4HC‘23
    Rajiv Movva, Divya Shanmugam, Kaihua Hou, Priya Pathak, John Guttag, Nikhil Garg, and Emma Pierson
    Machine Learning for Healthcare (ML4HC) (ML4HC‘23)
    ML4H Best Findings Paper (Honorable Mention), 2023 Cornell Chronicle
  25. 2022 C10
    Fair ranking: a critical review, challenges, and future directions
    FAccT‘22
    Gourab K Patro, Lorenzo Porcaro, Laura Mitchell, Qiuyue Zhang, Meike Zehlike, and Nikhil Garg
    ACM Conference on Fairness, Accountability, and Transparency (FAccT‘22)
    This work was written as part of a distributed, student-led working group of Mechanism Design for Social Good
  26. 2022 C9
    Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis
    FAccT‘22
    J.D. Zamfirescu-Pereira, Jerry Chen, Emily Wen, Allison Koenecke, Nikhil Garg, and Emma Pierson
    ACM Conference on Fairness, Accountability, and Transparency (FAccT‘22)
  27. 2022 C8
    Strategic Ranking
    AISTATS‘22
    Lydia T. Liu, Nikhil Garg, and Christian Borgs
    International Conference on Artificial Intelligence and Statistics (AISTATS‘22)
  28. 2021 C7
    Test-optional Policies: Overcoming Strategic Behavior and Informational Gaps
    EAAMO‘21
    Zhi Liu and Nikhil Garg
    AAAI/ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO‘21)
  29. 2021 C6
    The Stereotyping Problem in Collaboratively Filtered Recommender Systems
    EAAMO‘21
    Wenshuo Guo, Karl Krauth, Michael Jordan, and Nikhil Garg
    AAAI/ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO‘21)
  30. 2020 C5
    Fair Allocation through Selective Information Acquisition
    AIES‘20
    William Cai, Johann Gaebler, Nikhil Garg, and Sharad Goel
    AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES‘20)
  31. 2019 C4
    Who is in Your Top Three? Optimizing Learning in Elections with Many Candidates
    HCOMP‘19
    Nikhil Garg, Lodewijk L. Gelauff, Sukolsak Sakshuwong, and Ashish Goel
    AAAI Conference on Human Computation and Crowdsourcing (HCOMP‘19)
  32. 2019 C3
    Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings
    NAACL‘19
    Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Jesse Shapiro, Matthew Gentzkow, and Dan Jurafsky
    Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL‘19)
  33. 2019 C2
    Designing Optimal Binary Rating Systems
    AISTATS‘19
    Nikhil Garg and Ramesh Johari
    International Conference on Artificial Intelligence and Statistics (AISTATS‘19)
  34. 2015 C1
    Impact of Dual Slope Path Loss on User Association in HetNets
    IEEE Globecom Workshop
    Nikhil Garg, Sarabjot Singh, and Jeffrey Andrews
    IEEE Globecom Workshop (IEEE Globecom Workshop)

Other (workshops and technical reports)

  1. 2025 O6
    Optimizing Library Usage and Browser Experience: Application to the New York Public Library
    arxiv
    Zhi Liu, Wenchang Zhu, Sarah Rankin, and Nikhil Garg
  2. 2024 O5
    Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems
    arxiv
    Smitha Milli, Emma Pierson, and Nikhil Garg
  3. 2019 O4
    Deliberative Democracy with the Online Deliberation Platform
    HCOMP‘19 Demo
    James Fishkin, Nikhil Garg, Lodewijk Gelauff, Ashish Goel, Kamesh Munagala, Sukolsak Sakshuwong, Alice Siu, and Sravya Yandamuri
    AAAI Conference on Human Computation and Crowdsourcing Demo Track (HCOMP‘19 Demo)
  4. 2018 O3
    Comparing Voting Methods for Budget Decisions on the ASSU Ballot
    pdf
    Lodewijk Gelauff, Sukolsak Sakshuwong, Nikhil Garg, and Ashish Goel
  5. 2015 O2
    Fair Use and Innovation in Unlicensed Wireless Spectrum: LTE unlicensed and Wi-Fi in the 5 GHz unlicensed band
    IEEE-USA Journal of Technology and Public Policy
    Nikhil Garg
  6. 2015 O1
    Use of Electroencephalography and Galvanic Skin Response in the Prediction of an Attentive Cognitive State
    pdf
    Health and Human Performance Research Summit, Dayton, CO
    Beth Lewandowski, Kier Fortier, Nikhil Garg, Victor Rielly, Jeff Mackey, Tristan Hearn, Angela Harrivel, and Bradford Fenton

Theses

  1. 2020 T2
    Designing Marketplaces and Civic Engagement Platforms: Learning, Incentives, and Pricing
    Nikhil Garg
    PhD Dissertation, Stanford University INFORMS George Dantzig Dissertation Award, 2020 ACM SIGecom dissertation award (Honorable mention), 2021
  2. 2015 T1
    Downlink and Uplink User Association in Dense Next-Generation Wireless Networks
    Nikhil Garg
    Bachelors Thesis, University of Texas at Austin.

Contact me at ngarg@REMOVETHIScornell.REMOVETHISedu. Applicants: please read the information at the Contact page before emailing me.