World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
4209
World Ranking
12272
National Ranking
4972

Lirong Xia publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Lirong Xia sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 250 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 560 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 209 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Lirong Xia D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Lirong Xia sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

  • Profit-maximizing incentive for participatory sensing

    Tony Tie Luo;Hwee Pink Tan;Lirong Xia

  • Preference functions that score rankings and maximum likelihood estimation

    Vincent Conitzer;Matthew Rognlie;Lirong Xia

  • Sequential composition of voting rules in multi-issue domains

    Jérôme Lang;Lirong Xia

  • Complexity of unweighted coalitional manipulation under some common voting rules

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

  • Generalized scoring rules and the frequency of coalitional manipulability

    Lirong Xia;Vincent Conitzer

  • Computing the margin of victory for various voting rules

    Lirong Xia

  • Voting in Combinatorial Domains

    Jérôme Lang;Lirong Xia

  • Generalized Method-of-Moments for Rank Aggregation

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

  • A maximum likelihood approach towards aggregating partial orders

    Lirong Xia;Vincent Conitzer

  • A sufficient condition for voting rules to be frequently manipulable

    Lirong Xia;Vincent Conitzer

  • Random Utility Theory for Social Choice

    Hossein Azari Soufiani;David C. Parkes;Lirong Xia

  • Dominating manipulations in voting with partial information

    Vincent Conitzer;Toby Walsh;Lirong Xia

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

    David C. Parkes;Lirong Xia

  • Computing Parametric Ranking Models via Rank-Breaking

    Hossein Azari Soufiani;David Parkes;Lirong Xia

  • Random Utility Theory for Social Choice

    Hossein Azari;David Parks;Lirong Xia

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

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

  • Stackelberg voting games: computational aspects and paradoxes

    Lirong Xia;Vincent Conitzer

  • Incentive compatible budget elicitation in multi-unit auctions

    Sayan Bhattacharya;Vincent Conitzer;Kamesh Munagala;Lirong Xia

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

    Lirong Xia;Vincent Conitzer

  • 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

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

    Lirong Xia;Vincent Conitzer;Jérôme Lang

  • Preference elicitation for General Random Utility Models

    Hossein Azari Soufiani;David C. Parkes;Lirong Xia

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

    Lirong Xia;Jérôme Lang

Frequent Co-Authors

Vincent Conitzer
Vincent Conitzer Carnegie Mellon University
Jérôme Lang
Jérôme Lang Paris Dauphine University
Toby Walsh
Toby Walsh University of New South Wales
David C. Parkes
David C. Parkes Harvard University
Haris Aziz
Haris Aziz University of New South Wales
Malik Magdon-Ismail
Malik Magdon-Ismail Rensselaer Polytechnic Institute
Mingsheng Ying
Mingsheng Ying University of Technology Sydney
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Kenneth Holmqvist
Kenneth Holmqvist University of Regensburg
Ariel D. Procaccia
Ariel D. Procaccia Harvard University

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