World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
8021
World Ranking
7971
National Ranking
3433

Yiling Chen 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 Yiling Chen 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: 249 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: 559 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: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 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: 148 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Yiling Chen 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 Yiling Chen sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Yiling Chen is affiliated with Harvard University in the United States and has contributed research primarily in the field of Economics, Econometrics and Finance. Their work spans several interconnected subfields, including Economics and Econometrics, Management Science and Operations Research, Finance, Accounting, and Urban Studies.

Their research covers a variety of topics, with particular focus on Corporate Finance and Governance, Auction Theory and Applications, Housing, Finance, and Neoliberalism, Urban Planning and Governance, Innovation Policy and R&D, Energy, Environment and Economic Growth, and Sports Analytics and Performance.

Yiling Chen has published multiple papers in respected journals and platforms. Notable recent publications include:

  • "Effectiveness of industrial policy in supporting innovation: the role of internal and external corporate governance mechanism," 2021, Applied Economics
  • "Alternative gentrification: coexistence of traditional and new industries in historic districts through transfer of development rights in Dihua Street, Taiwan," 2023, International Journal of Heritage Studies
  • "Housing Prices Never Fall": The Development of Housing Finance in Taiwan," 2020, Housing Policy Debate
  • "Government support and bank performance during the 2007-2008 financial crisis," 2020, The North American Journal of Economics and Finance

Other frequently used publication venues include arXiv (Cornell University) and SSRN Electronic Journal, where several works have appeared.

Frequent collaborators in their research include Fuyuan Zhang, Jianghong Cai, X. Zhu, Rong Fu, and Zhongxiao Lin, each appearing as coauthors in multiple publications.

Best Publications

  • Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015

    Colin F. Camerer;Anna Dreber;Felix Holzmeister;Teck-Hua Ho

  • Using internet searches for influenza surveillance.

    Philip M. Polgreen;Yiling Chen;David M. Pennock;Forrest D. Nelson

  • Using prediction markets to estimate the reproducibility of scientific research

    Anna Dreber;Thomas Pfeiffer;Johan Almenberg;Siri Isaksson

  • The Principles and Limits of Algorithm-in-the-Loop Decision Making

    Ben Green;Yiling Chen

  • Disparate Interactions: An Algorithm-in-the-Loop Analysis of Fairness in Risk Assessments

    Ben Green;Yiling Chen

  • Truth, justice, and cake cutting

    Yiling Chen;John K. Lai;David C. Parkes;Ariel D. Procaccia

  • A Utility Framework for Bounded-Loss Market Makers

    Yiling Chen;David M Pennock

  • Designing incentives for online question and answer forums

    Shaili Jain;Yiling Chen;David C. Parkes

  • Better human computation through principled voting

    Andrew Mao;Ariel D. Procaccia;Yiling Chen

  • Volunteering Versus Work for Pay: Incentives and Tradeoffs in Crowdsourcing

    Andrew Mao;Ece Kamar;Yiling Chen;Eric Horvitz

  • A Short-term Intervention for Long-term Fairness in the Labor Market

    Lily Hu;Yiling Chen

  • Gaming Prediction Markets: Equilibrium Strategies with a Market Maker

    Yiling Chen;Stanko Dimitrov;Rahul Sami;Daniel M. Reeves

  • A new understanding of prediction markets via no-regret learning

    Yiling Chen;Jennifer Wortman Vaughan

  • Information markets vs. opinion pools: an empirical comparison

    Yiling Chen;Chao-Hsien Chu;Tracy Mullen;David M. Pennock

  • Truthful mechanisms for agents that value privacy

    Yiling Chen;Stephen Chong;Ian A. Kash;Tal Moran

  • Toward automatic task design: a progress report

    Eric Huang;Haoqi Zhang;David C. Parkes;Krzysztof Z. Gajos

  • Predicting replication outcomes in the Many Labs 2 study

    Eskil Forsell;Domenico Viganola;Thomas Pfeiffer;Johan Almenberg

  • Efficient Market Making via Convex Optimization, and a Connection to Online Learning

    Jacob Abernethy;Yiling Chen;Jennifer Wortman Vaughan

  • Output Agreement Mechanisms and Common Knowledge

    Bo Franklin Waggoner;Yiling Chen

  • Designing Markets for Prediction

    Yiling Chen;David M. Pennock

  • Fair classification and social welfare

    Lily Hu;Yiling Chen

  • Learning Strategy-Aware Linear Classifiers

    Yiling Chen;Yang Liu;Chara Podimata

Frequent Co-Authors

David C. Parkes
David C. Parkes Harvard University
Anna Dreber
Anna Dreber Stockholm School of Economics
David M. Pennock
David M. Pennock Rutgers, The State University of New Jersey
Brian A. Nosek
Brian A. Nosek Center for Open Science
Ariel D. Procaccia
Ariel D. Procaccia Harvard University
Magnus Johannesson
Magnus Johannesson Stockholm School of Economics
Lance Fortnow
Lance Fortnow Illinois Institute of Technology
Michael P. Bishop
Michael P. Bishop Texas A&M University
Nicole Immorlica
Nicole Immorlica Microsoft (United States)
Chao-Hsien Chu
Chao-Hsien Chu Pennsylvania State University

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