2026 Lirong Xia: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	34	12272	11915	4972	4748	209	4209

Overview

Lirong Xia is affiliated with Rutgers, The State University of New Jersey in the United States. Their research spans multiple fields including Computer Science, Economics, Econometrics and Finance, and Decision Sciences, with a strong focus on interdisciplinary applications.

Their work is mainly concentrated in the following subfields:

Artificial Intelligence
Economics and Econometrics
Management Science and Operations Research
Safety Research
General Decision Sciences

The core topics addressed in their research include:

Game Theory and Voting Systems
Auction Theory and Applications
Internet Traffic Analysis and Secure E-voting
Logic, Reasoning, and Knowledge
Experimental Behavioral Economics Studies
Privacy-Preserving Technologies in Data
Adversarial Robustness in Machine Learning

Lirong Xia has contributed several papers to prominent academic venues. Selected recent publications include:

A Complexity-of-Strategic-Behavior Comparison between Schulze's Rule and Ranked Pairs, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
Optimized collusion prevention for online exams during social distancing, 2021, npj Science of Learning
Let It Snow: Adding pixel noise to protect the user's identity, 2020, ACM Symposium on Eye Tracking Research and Applications
Fair Division Through Information Withholding, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
Fair and Efficient Allocations under Lexicographic Preferences, 2021, Proceedings of the AAAI Conference on Artificial Intelligence

The most frequent publication venues where their work appears are:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
Journal of Artificial Intelligence Research
Artificial Intelligence
npj Science of Learning

Collaborations have been an integral part of their academic output, with frequent coauthors including:

Sujoy Sikdar
Yongzhi Cao
Hanpin Wang
Rohit Vaish
Ao Liu

Best Publications

Determining possible and necessary winners under common voting rules given partial orders

Lirong Xia;Vincent Conitzer

321
Citations
Profit-maximizing incentive for participatory sensing

Tony Tie Luo;Hwee Pink Tan;Lirong Xia

225
Citations
Preference functions that score rankings and maximum likelihood estimation

Vincent Conitzer;Matthew Rognlie;Lirong Xia

190
Citations
Sequential composition of voting rules in multi-issue domains

Jérôme Lang;Lirong Xia

146
Citations
Complexity of unweighted coalitional manipulation under some common voting rules

Lirong Xia;Michael Zuckerman;Ariel D. Procaccia;Vincent Conitzer

137
Citations
Generalized scoring rules and the frequency of coalitional manipulability

Lirong Xia;Vincent Conitzer

126
Citations
Computing the margin of victory for various voting rules

Lirong Xia

117
Citations
Voting in Combinatorial Domains

Jérôme Lang;Lirong Xia

108
Citations
Generalized Method-of-Moments for Rank Aggregation

Hossein Azari Soufiani;William Chen;David C Parkes;Lirong Xia

107
Citations
A maximum likelihood approach towards aggregating partial orders

Lirong Xia;Vincent Conitzer

87
Citations
A sufficient condition for voting rules to be frequently manipulable

Lirong Xia;Vincent Conitzer

84
Citations
Random Utility Theory for Social Choice

Hossein Azari Soufiani;David C. Parkes;Lirong Xia

83
Citations
Dominating manipulations in voting with partial information

Vincent Conitzer;Toby Walsh;Lirong Xia

82
Citations
A complexity-of-strategic-behavior comparison between Schulze's rule and ranked pairs

David C. Parkes;Lirong Xia

82
Citations
Computing Parametric Ranking Models via Rank-Breaking

Hossein Azari Soufiani;David Parkes;Lirong Xia

76
Citations
Random Utility Theory for Social Choice

Hossein Azari;David Parks;Lirong Xia

74
Citations
Incentive Mechanism Design for Crowdsourcing: An All-Pay Auction Approach

Tie Luo;Sajal K. Das;Hwee Pink Tan;Lirong Xia

73
Citations
Stackelberg voting games: computational aspects and paradoxes

Lirong Xia;Vincent Conitzer

71
Citations
Incentive compatible budget elicitation in multi-unit auctions

Sayan Bhattacharya;Vincent Conitzer;Kamesh Munagala;Lirong Xia

70
Citations
Determining possible and necessary winners under common voting rules given partial orders

Lirong Xia;Vincent Conitzer

69
Citations
New candidates welcome! Possible winners with respect to the addition of new candidates

Yann Chevaleyre;Jérôme Lang;Jérôme Lang;Nicolas Maudet;Jérôme Monnot;Jérôme Monnot

66
Citations
Aggregating preferences in multi-issue domains by using maximum likelihood estimators

Lirong Xia;Vincent Conitzer;Jérôme Lang

64
Citations
Preference elicitation for General Random Utility Models

Hossein Azari Soufiani;David C. Parkes;Lirong Xia

53
Citations
A dichotomy theorem on the existence of efficient or neutral sequential voting correspondences

Lirong Xia;Jérôme Lang

7
Citations

Frequent Co-Authors

Vincent Conitzer Carnegie Mellon University

Jérôme Lang Paris Dauphine University

Toby Walsh University of New South Wales

David C. Parkes Harvard University

Haris Aziz University of New South Wales

Malik Magdon-Ismail Rensselaer Polytechnic Institute

Mingsheng Ying University of Technology Sydney

Tie-Yan Liu Microsoft (United States)

Kenneth Holmqvist University of Regensburg

Ariel D. Procaccia Harvard University

External Links

Personal website of Lirong Xia

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