World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
19602
World Ranking
3018
National Ranking
1480

Yu Cheng 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 Yu Cheng 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: 331 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Yu Cheng 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 Yu Cheng 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: 61 D-Index — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Overview

Yu Cheng is affiliated with Microsoft in the United States and has contributed extensively to the field of computer science, with a focus on artificial intelligence and related subfields.

The scientist has published a total of 55 papers, primarily in the following main and subfields of study:

  • Computer Science
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Psychiatry and Mental Health
  • Economics and Econometrics

Their research covers a range of topics including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Adversarial Robustness in Machine Learning
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications
  • Anomaly Detection Techniques and Applications
  • Image and Signal Denoising Methods

Yu Cheng has frequently published in several venues, most notably:

  • arXiv (Cornell University)
  • IEEE Transactions on Image Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Neural Networks and Learning Systems
  • Displays

Some representative recent papers authored or co-authored by Yu Cheng include:

  • EnlightenGAN: Deep Light Enhancement Without Paired Supervision, 2021, IEEE Transactions on Image Processing
  • DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models, 2023, arXiv (Cornell University)
  • Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning, 2020, arXiv (Cornell University)
  • Efficient Robust Training via Backward Smoothing, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling, 2020, IEEE Transactions on Neural Networks and Learning Systems

Yu Cheng has collaborated frequently with several co-authors, including:

  • Zhe Gan
  • Zhangyang Wang
  • Shuohang Wang
  • Tianlong Chen
  • Jingjing Liu

Best Publications

  • EnlightenGAN: Deep Light Enhancement Without Paired Supervision

    Yifan Jiang;Xinyu Gong;Ding Liu;Yu Cheng

  • UNITER: UNiversal Image-TExt Representation Learning

    Yen-Chun Chen;Linjie Li;Licheng Yu;Ahmed El Kholy

  • A Survey of Model Compression and Acceleration for Deep Neural Networks

    Yu Cheng;Duo Wang;Pan Zhou;Tao Zhang

  • Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges

    Yu Cheng;Duo Wang;Pan Zhou;Tao Zhang

  • Deep Model Based Domain Adaptation for Fault Diagnosis

    Weining Lu;Bin Liang;Yu Cheng;Deshan Meng

  • Patient Knowledge Distillation for BERT Model Compression

    Siqi Sun;Yu Cheng;Zhe Gan;Jingjing Liu

  • MMD GAN: Towards Deeper Understanding of Moment Matching Network

    Chun-Liang Li;Wei-Cheng Chang;Yu Cheng;Yiming Yang

  • Risk Prediction with Electronic Health Records: A Deep Learning Approach.

    Yu Cheng;Fei Wang;Ping Zhang;Jianying Hu

  • HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training

    Linjie Li;Yen-Chun Chen;Yu Cheng;Zhe Gan

  • Fully-Adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification

    Yongxi Lu;Abhishek Kumar;Shuangfei Zhai;Yu Cheng

  • Relation-Aware Graph Attention Network for Visual Question Answering

    Linjie Li;Zhe Gan;Yu Cheng;Jingjing Liu

  • UNITER: Learning UNiversal Image-TExt Representations

    Yen-Chun Chen;Linjie Li;Licheng Yu;Ahmed El Kholy

  • Jointly Attentive Spatial-Temporal Pooling Networks for Video-Based Person Re-identification

    Shuangjie Xu;Yu Cheng;Kang Gu;Yang Yang

  • Deep structured energy based models for anomaly detection

    Shuangfei Zhai;Yu Cheng;Weining Lu;Zhongfei Zhang

  • An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections

    Yu Cheng;Yu Cheng;Felix X. Yu;Rogerio S. Feris;Sanjiv Kumar

  • Large-Scale Adversarial Training for Vision-and-Language Representation Learning

    Zhe Gan;Yen-Chun Chen;Linjie Li;Chen Zhu

  • Towards Pose Invariant Face Recognition in the Wild

    Jian Zhao;Yu Cheng;Yan Xu;Lin Xiong

  • Discourse-Aware Neural Extractive Text Summarization

    Jiacheng Xu;Zhe Gan;Yu Cheng;Jingjing Liu

  • Diverse Few-Shot Text Classification with Multiple Metrics

    Mo Yu;Xiaoxiao Guo;Jinfeng Yi;Shiyu Chang

  • Occlusion-Aware Networks for 3D Human Pose Estimation in Video

    Yu Cheng;Bo Yang;Bo Wang;Yan Wending

  • StoryGAN: A Sequential Conditional GAN for Story Visualization

    Yitong Li;Zhe Gan;Yelong Shen;Jingjing Liu

Frequent Co-Authors

Zhe Gan
Zhe Gan Microsoft (United States)
Alok Choudhary
Alok Choudhary Northwestern University
Ankit Agrawal
Ankit Agrawal Northwestern University
Shuohang Wang
Shuohang Wang Microsoft (United States)
Rogerio Feris
Rogerio Feris IBM (United States)
Pan Zhou
Pan Zhou Huazhong University of Science and Technology
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Licheng Yu
Licheng Yu Facebook (United States)
Xiaoxiao Guo
Xiaoxiao Guo The University of Texas at Dallas

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