World's Best Scientists 2026 revealed!
Mingsheng Long

Mingsheng Long

D-Index & Metrics

Computer Science

D-Index
64
Citations
29190
World Ranking
2522
National Ranking
341

Mingsheng Long 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 Mingsheng Long 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: 118 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Mingsheng Long 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 Mingsheng Long 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: 64 D-Index — 82nd percentile

82% of scientists in this discipline score the same or lower.

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

Overview

Mingsheng Long is affiliated with Tsinghua University in China and specializes in the field of Computer Science. Their research contributions span multiple subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Management Science and Operations Research, and Atmospheric Science.

Their scholarly work has focused on several main topics, with notable emphasis on Domain Adaptation and Few-Shot Learning, Time Series Analysis and Forecasting, Multimodal Machine Learning Applications, Human Pose and Action Recognition, Topic Modeling, Machine Learning and Data Classification, and Stock Market Forecasting Methods.

Frequent co-authors collaborating with Mingsheng Long include Jianmin Wang, Haixu Wu, Ximei Wang, Zhangjie Cao, and Yunbo Wang.

The scientist has published extensively in various venues. The most frequent publication forums include:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Scientia Sinica Informationis
  • Nature

Recent papers authored or co-authored by Mingsheng Long include:

  • "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting," 2021, arXiv (Cornell University)
  • "PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning," 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis," 2022, arXiv (Cornell University)
  • "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting," 2023, arXiv (Cornell University)

Their research often addresses complex problems in time series forecasting and spatiotemporal predictive learning, with a focus on transformer-based architectures and recurrent neural networks.

Best Publications

  • Learning Transferable Features with Deep Adaptation Networks

    Mingsheng Long;Mingsheng Long;Yue Cao;Jianmin Wang;Michael Jordan

  • Transfer Feature Learning with Joint Distribution Adaptation

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Jiaguang Sun

  • Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting

    haixu wu;Jiehui Xu;Jianmin Wang;Mingsheng Long

  • Deep transfer learning with joint adaptation networks

    Mingsheng Long;Han Zhu;Jianmin Wang;Michael I. Jordan

  • Conditional Adversarial Domain Adaptation

    Mingsheng Long;Zhangjie Cao;Jianmin Wang;Michael I. Jordan

  • Unsupervised domain adaptation with residual transfer networks

    Mingsheng Long;Han Zhu;Jianmin Wang;Michael I. Jordan

  • Multi-Adversarial Domain Adaptation

    Zhongyi Pei;Zhangjie Cao;Mingsheng Long;Jianmin Wang

  • Transfer Joint Matching for Unsupervised Domain Adaptation

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Jiaguang Sun

  • HashNet: Deep Learning to Hash by Continuation

    Zhangjie Cao;Mingsheng Long;Jianmin Wang;Philip S. Yu

  • Deep Hashing Network for efficient similarity retrieval

    Han Zhu;Mingsheng Long;Jianmin Wang;Yue Cao

  • Adaptation Regularization: A General Framework for Transfer Learning

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Sinno Jialin Pan

  • PredRNN: recurrent neural networks for predictive learning using spatiotemporal LSTMs

    Yunbo Wang;Mingsheng Long;Jianmin Wang;Zhifeng Gao

  • Transferable Representation Learning with Deep Adaptation Networks

    Mingsheng Long;Yue Cao;Zhangjie Cao;Jianmin Wang

  • PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning

    Yunbo Wang;Haixu Wu;Jianjin Zhang;Zhifeng Gao

  • Partial Adversarial Domain Adaptation

    Zhangjie Cao;Lijia Ma;Mingsheng Long;Jianmin Wang

  • Partial Transfer Learning with Selective Adversarial Networks

    Zhangjie Cao;Mingsheng Long;Jianmin Wang;Michael I. Jordan

  • Universal Domain Adaptation

    Kaichao You;Mingsheng Long;Zhangjie Cao;Jianmin Wang

  • Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics

    Yunbo Wang;Jianjin Zhang;Hongyu Zhu;Mingsheng Long

  • Transfer Learning with Graph Co-Regularization

    Mingsheng Long;Jianmin Wang;Guiguang Ding;Dou Shen

  • Deep Cauchy Hashing for Hamming Space Retrieval

    Yue Cao;Mingsheng Long;Bin Liu;Jianmin Wang

  • Bridging Theory and Algorithm for Domain Adaptation.

    Yuchen Zhang;Tianle Liu;Mingsheng Long;Michael I. Jordan

  • Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

    Xinyang Chen;Sinan Wang;Mingsheng Long;Jianmin Wang

  • Eidetic 3D LSTM: A Model for Video Prediction and Beyond

    Yunbo Wang;Yunbo Wang;Lu Jiang;Ming Hsuan Yang;Li Jia Li

Frequent Co-Authors

Jianmin Wang
Jianmin Wang Tsinghua University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Guiguang Ding
Guiguang Ding Tsinghua University
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Han Hu
Han Hu Microsoft Research Asia (China)
Jingdong Wang
Jingdong Wang Baidu (China)
Xiang Zhang
Xiang Zhang University of Hong Kong
Li Fei-Fei
Li Fei-Fei Stanford University
Jiajun Wu
Jiajun Wu Stanford University

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