World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
87
Citations
26583
World Ranking
735
National Ranking
112

Yu Qiao 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 Qiao 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: 193 publications — 44th percentile

44% of scientists in this discipline score the same or lower.

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

Yu Qiao 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 Qiao 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: 87 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Overview

Yu Qiao is a researcher affiliated with the Chinese Academy of Sciences in China, focused on engineering with extensive work in biomedical engineering, mechanical engineering, building and construction, safety, risk, reliability and quality, and materials chemistry. Their primary research interests cover thermochemical biomass conversion processes, recycling and utilization of industrial and municipal waste in materials production, lignin and wood chemistry, fire dynamics and safety research, coal and its by-products, supercapacitor materials and fabrication, and catalysis and hydrodesulfurization studies.

Yu Qiao has published numerous papers in a range of scientific journals. Some recent publications include:

  • Transformation of nitrogen during hydrothermal carbonization of sewage sludge: Effects of temperature and Na/Ca acetates addition, 2020, Proceedings of the Combustion Institute
  • Co-hydrothermal carbonization of sewage sludge and model compounds of food waste: Influence of mutual interaction on nitrogen transformation, 2021, The Science of The Total Environment
  • Smouldering combustion of sewage sludge: Volumetric scale-up, product characterization, and economic analysis, 2021, Fuel
  • Valorization of Food Waste via Torrefaction: Effect of Food Waste Type on the Characteristics of Torrefaction Products, 2020, Energy & Fuels
  • Thermodynamic and techno-economic analysis of hydrogen production from food waste by torrefaction integrated with steam gasification, 2023, Energy Conversion and Management

The frequent co-authors collaborating with Yu Qiao are:

  • Jingchun Huang
  • Zhenqi Wang
  • Minghou Xu
  • Di Xie
  • Wei Hu

Yu Qiao's research is often published in specific scientific venues. The most common publication journals include:

  • Fuel
  • SSRN Electronic Journal
  • Proceedings of the Combustion Institute
  • Energy & Fuels
  • The Science of The Total Environment

The scientist's body of work is concentrated primarily in the field of engineering, with an emphasis on thermochemical and environmental processes involving biomass conversion, waste recycling, and energy production. Their research covers interdisciplinary topics addressing both fundamental chemical processes and applied technologies in energy and environmental engineering.

Best Publications

  • Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks

    Kaipeng Zhang;Zhanpeng Zhang;Zhifeng Li;Yu Qiao

  • Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • A Discriminative Feature Learning Approach for Deep Face Recognition

    Yandong Wen;Kaipeng Zhang;Zhifeng Li;Yu Qiao

  • NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

    Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang

  • Bevformer: learning bird's-eye-view representation from lidar-camera via spatiotemporal transformers

    Unknown

  • ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

    Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu

  • Detecting Text in Natural Image with Connectionist Text Proposal Network

    Zhi Tian;Weilin Huang;Weilin Huang;Tong He;Pan He

  • Internimage: Exploring large-scale vision foundation models with deformable convolutions

    Unknown

  • Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition

    Kai Wang;Xiaojiang Peng;Jianfei Yang;Debin Meng

  • Llama-adapter: Efficient fine-tuning of language models with zero-init attention

    Unknown

  • Animatediff: Animate your personalized text-to-image diffusion models without specific tuning

    Unknown

  • Planning-oriented autonomous driving

    Unknown

  • Videochat: Chat-centric video understanding

    Unknown

  • Vision transformer adapter for dense predictions

    Unknown

  • Llama-adapter v2: Parameter-efficient visual instruction model

    Unknown

  • Towards Good Practices for Very Deep Two-Stream ConvNets

    Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao

  • Pointclip: Point cloud understanding by clip

    Unknown

  • How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites

    Unknown

  • Visionllm: Large language model is also an open-ended decoder for vision-centric tasks

    Unknown

  • Efficient image super-resolution using pixel attention

    Unknown

  • Uniformer: Unifying convolution and self-attention for visual recognition

    Unknown

  • Videomae v2: Scaling video masked autoencoders with dual masking

    Unknown

  • Tip-adapter: Training-free adaption of clip for few-shot classification

    Unknown

  • Internvideo: General video foundation models via generative and discriminative learning

    Unknown

  • Mvbench: A comprehensive multi-modal video understanding benchmark

    Unknown

  • Uniformer: Unified transformer for efficient spatiotemporal representation learning

    Unknown

  • Vbench: Comprehensive benchmark suite for video generative models

    Unknown

  • Bevformer v2: Adapting modern image backbones to bird's-eye-view recognition via perspective supervision

    Unknown

Frequent Co-Authors

Haoshen Zhou
Haoshen Zhou Nanjing University
Limin Wang
Limin Wang Nanjing University
Minghou Xu
Minghou Xu Huazhong University of Science and Technology
Xiaoou Tang
Xiaoou Tang Chinese University of Hong Kong
Chao Dong
Chao Dong Shenzhen Institutes of Advanced Technology
Zhifeng Li
Zhifeng Li Tencent (China)
Ping He
Ping He Nanjing University
Hong Yao
Hong Yao Huazhong University of Science and Technology
Luc Van Gool
Luc Van Gool Institute for Computer Science, Artificial Intelligence and Technology (INSAIT)
Jianfei Yang
Jianfei Yang Nanyang Technological University

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