Nikhil Garg

Nikhil Garg

University of California, Berkeley

H-index: 13

North America-United States

About Nikhil Garg

Nikhil Garg, With an exceptional h-index of 13 and a recent h-index of 12 (since 2020), a distinguished researcher at University of California, Berkeley, specializes in the field of economics and computation, urban systems, artificial intelligence, market design.

His recent articles reflect a diverse array of research interests and contributions to the field:

Supply-side equilibria in recommender systems

Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing

Wisdom and Foolishness of Noisy Matching Markets

Interface Design to Mitigate Inflation in Recommender Systems

Faster Information for Effective Long-term Discharge: A Field Study in Adult Foster Care

Reconciling the accuracy-diversity trade-off in recommendations

Coarse race data conceals disparities in clinical risk score performance

Nikhil Garg Information

University

Position

Postdoc

Citations(all)

1648

Citations(since 2020)

1595

Cited By

553

hIndex(all)

13

hIndex(since 2020)

12

i10Index(all)

15

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Nikhil Garg Skills & Research Interests

economics and computation

urban systems

artificial intelligence

market design

Top articles of Nikhil Garg

Title

Journal

Author(s)

Publication Date

Supply-side equilibria in recommender systems

Advances in Neural Information Processing Systems

Meena Jagadeesan

Nikhil Garg

Jacob Steinhardt

2024/2/13

Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling

Proceedings of the AAAI Conference on Artificial Intelligence

Zhi Liu

Sarah Rankin

Nikhil Garg

2024/3/24

A Bayesian Spatial Model to Correct Under-Reporting in Urban Crowdsourcing

Proceedings of the AAAI Conference on Artificial Intelligence

Gabriel Agostini

Emma Pierson

Nikhil Garg

2024/3/24

Wisdom and Foolishness of Noisy Matching Markets

arXiv preprint arXiv:2402.16771

Kenny Peng

Nikhil Garg

2024/2/26

Interface Design to Mitigate Inflation in Recommender Systems

Rana Shahout

Yehonatan Peisakhovsky

Sasha Stoikov

Nikhil Garg

2023/9/14

Faster Information for Effective Long-term Discharge: A Field Study in Adult Foster Care

VINCE BARTLE

NICOLA DELL

NIKHIL GARG

2023

Reconciling the accuracy-diversity trade-off in recommendations

arXiv preprint arXiv:2307.15142

Kenny Peng

Manish Raghavan

Emma Pierson

Jon Kleinberg

Nikhil Garg

2023/7/27

Coarse race data conceals disparities in clinical risk score performance

Rajiv Movva

Divya Shanmugam

Kaihua Hou

Priya Pathak

John Guttag

...

2023/12/22

Monoculture in Matching Markets

arXiv preprint arXiv:2312.09841

Kenny Peng

Nikhil Garg

2023/12/15

Large language models shape and are shaped by society: A survey of arXiv publication patterns

arXiv preprint arXiv:2307.10700

Rajiv Movva

Sidhika Balachandar

Kenny Peng

Gabriel Agostini

Nikhil Garg

...

2023/7/20

Domain constraints improve risk prediction when outcome data is missing

arXiv preprint arXiv:2312.03878

Sidhika Balachandar

Nikhil Garg

Emma Pierson

2023/12/6

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

arXiv preprint arXiv:2307.08774

Lily Xu

Esther Rolf

Sara Beery

Joseph R Bennett

Tanya Berger-Wolf

...

2023/7/17

Quantifying spatial under-reporting disparities in resident crowdsourcing

Nature Computational Science

Zhi Liu

Uma Bhandaram

Nikhil Garg

2023/12/5

Choosing the Right Weights: Balancing Value, Strategy, and Noise in Recommender Systems

arXiv preprint arXiv:2305.17428

Smitha Milli

Emma Pierson

Nikhil Garg

2023/5/27

Strategic ranking

Lydia T Liu

Nikhil Garg

Christian Borgs

2022/5/3

End-to-end Auditing for Decision Pipelines.

ICML Workshop on Responsible Decision Making in Dynamic Environments (RDMDE)

Benjamin Laufer

Emma Pierson

Nikhil Garg

2022/1

Combatting Gerrymandering with Social Choice: The Design of Multi-member Districts

Nikhil Garg

Wes Gurnee

David Rothschild

David Shmoys

2022/7/12

Balancing Producer Fairness and Efficiency via Bayesian Rating System Design

arXiv preprint arXiv:2207.04369

Thomas Ma

Michael S Bernstein

Ramesh Johari

Nikhil Garg

2022/7/10

Trucks Don’t Mean Trump: Diagnosing Human Error in Image Analysis

JD Zamfirescu-Pereira

Jerry Chen

Emily Wen

Allison Koenecke

Nikhil Garg

...

2022/6/21

Fair ranking: a critical review, challenges, and future directions

Gourab K Patro

Lorenzo Porcaro

Laura Mitchell

Qiuyue Zhang

Meike Zehlike

...

2022/6/21

See List of Professors in Nikhil Garg University(University of California, Berkeley)

Co-Authors

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