World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
22727
World Ranking
2279
National Ranking
313

Weinan Zhang 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 Weinan Zhang 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: 293 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Weinan Zhang 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 Weinan Zhang 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: 66 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

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

Overview

Weinan Zhang is affiliated with Shanghai Jiao Tong University in China and has a research portfolio primarily centered in the field of Computer Science. Their work spans various subfields including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Molecular Biology.

Their research topics cover a range of areas with a notable emphasis on Recommender Systems and Techniques, Topic Modeling, Reinforcement Learning in Robotics, Advanced Graph Neural Networks, Natural Language Processing Techniques, Advanced Bandit Algorithms Research, and Multimodal Machine Learning Applications.

Frequent coauthors in Weinan Zhang's work include:

  • Yong Yu
  • Ruiming Tang
  • Weiwen Liu
  • Yunjia Xi

Common publication venues where Weinan Zhang's research appears include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • ACM Transactions on Information Systems
  • Frontiers of Computer Science

Representative recent papers authored include:

  • GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation, 2020, arXiv (Cornell University)
  • Spatio-Temporal Meta Learning for Urban Traffic Prediction, 2020, IEEE Transactions on Knowledge and Data Engineering
  • Towards Making the Most of BERT in Neural Machine Translation, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • SMARTS: Scalable Multi-Agent Reinforcement Learning Training School for Autonomous Driving, 2020, arXiv (Cornell University)
  • How Can Recommender Systems Benefit from Large Language Models: A Survey, 2024, ACM Transactions on Information Systems

Best Publications

  • Seqgan: sequence generative adversarial nets with policy gradient

    Lantao Yu;Weinan Zhang;Jun Wang;Yong Yu

  • Wasserstein Distance Guided Representation Learning for Domain Adaptation

    Jian Shen;Yanru Qu;Weinan Zhang;Yong Yu

  • IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models

    Jun Wang;Lantao Yu;Weinan Zhang;Yu Gong

  • Product-Based Neural Networks for User Response Prediction

    Yanru Qu;Han Cai;Kan Ren;Weinan Zhang

  • GraphGAN: Graph Representation Learning With Generative Adversarial Nets.

    Hongwei Wang;Jia Wang;Jialin Wang;Miao Zhao

  • Efficient Architecture Search by Network Transformation

    Han Cai;Tianyao Chen;Weinan Zhang;Yong Yu

  • Long Text Generation via Adversarial Training with Leaked Information

    Jiaxian Guo;Sidi Lu;Han Cai;Weinan Zhang

  • Deep Learning over Multi-field Categorical Data

    Weinan Zhang;Tianming Du;Jun Wang

  • Texygen: A Benchmarking Platform for Text Generation Models

    Yaoming Zhu;Sidi Lu;Lei Zheng;Jiaxian Guo

  • Mean Field Multi-Agent Reinforcement Learning

    Yaodong Yang;Rui Luo;Minne Li;Ming Zhou

  • CoLight: Learning Network-level Cooperation for Traffic Signal Control

    Hua Wei;Nan Xu;Huichu Zhang;Guanjie Zheng

  • Deep learning over Multi-Field categorical Data - A case study on user response prediction

    Weinan Zhang;Tianming Du;Jun Wang

  • Optimal real-time bidding for display advertising

    Weinan Zhang;Shuai Yuan;Jun Wang

  • Real-Time Bidding by Reinforcement Learning in Display Advertising

    Han Cai;Kan Ren;Weinan Zhang;Kleanthis Malialis

  • CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

    Huichu Zhang;Siyuan Feng;Chang Liu;Yaoyao Ding

  • SVDFeature: a toolkit for feature-based collaborative filtering

    Tianqi Chen;Weinan Zhang;Qiuxia Lu;Kailong Chen

  • Optimizing top-n collaborative filtering via dynamic negative item sampling

    Weinan Zhang;Tianqi Chen;Jun Wang;Yong Yu

  • Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data

    Yanru Qu;Bohui Fang;Weinan Zhang;Ruiming Tang

  • GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation

    Chence Shi;Minkai Xu;Zhaocheng Zhu;Weinan Zhang

  • Display Advertising with Real-Time Bidding (Rtb) and Behavioural Targeting

    Jun Wang;Weinan Zhang;Shuai Yuan

  • Interactive collaborative filtering

    Xiaoxue Zhao;Weinan Zhang;Jun Wang

  • Path-Level Network Transformation for Efficient Architecture Search.

    Han Cai;Jiacheng Yang;Weinan Zhang;Song Han

Frequent Co-Authors

Yong Yu
Yong Yu Shanghai Jiao Tong University
Xiuqiang He
Xiuqiang He Huawei Technologies (China)
Xinbing Wang
Xinbing Wang Shanghai Jiao Tong University
Alexander J. Smola
Alexander J. Smola Amazon (United States)
Jian Tang
Jian Tang Syracuse University
Joemon M. Jose
Joemon M. Jose University of Glasgow
Zheng Zhang
Zheng Zhang New York University Shanghai
Diyi Yang
Diyi Yang Stanford University
Zhenhui Li
Zhenhui Li Pennsylvania State University
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)

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