World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
11290
World Ranking
3885
National Ranking
520

Shanlin Yang 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 Shanlin Yang 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: 199 publications — 46th percentile

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

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

Shanlin Yang 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 Shanlin Yang 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: 57 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Overview

Shanlin Yang is affiliated with the Hefei University of Technology in China. Their research spans several interconnected areas primarily within Engineering and Computer Science, with a notable focus on electrical and electronic engineering, management science and operations research, and artificial intelligence.

The scientist has contributed extensively to topics such as smart grid energy management, multi-criteria decision making, energy load and power forecasting, as well as scheduling and timetabling solutions. Additional research interests include rough sets and fuzzy logic, energy-environment-economic growth intersections, and healthcare operations and scheduling optimization.

Shanlin Yang's publication record includes articles in venues such as IEEE Transactions on Industrial Informatics, arXiv (Cornell University), IEEE Transactions on Instrumentation and Measurement, SSRN Electronic Journal, and Applied Energy. These frequent publication venues reflect the breadth of their expertise across industrial informatics, energy systems, and applied research.

Among recent publications are:

  • Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment, 2020, Applied Energy
  • A robust optimization approach for coordinated operation of multiple energy hubs, 2020, Energy
  • Unsupervised-Learning-Based Continuous Depth and Motion Estimation With Monocular Endoscopy for Virtual Reality Minimally Invasive Surgery, 2020, IEEE Transactions on Industrial Informatics
  • Multiple criteria group decision making based on group satisfaction, 2020, Information Sciences
  • The driving effect of technological innovation on green development: From the perspective of efficiency, 2024, Energy Policy

Several collaborators frequently co-author works with Shanlin Yang. These include Kaile Zhou, Shuai Ding, Chao Fu, Wenjuan Fan, and Pãnos M. Pardalos. These partnerships indicate a collaborative network spanning multiple research domains relevant to their fields.

Best Publications

  • Big data driven smart energy management: From big data to big insights

    Kaile Zhou;Chao Fu;Shanlin Yang

  • A hybrid deep learning model for short-term PV power forecasting

    Pengtao Li;Pengtao Li;Kaile Zhou;Kaile Zhou;Xinhui Lu;Xinhui Lu;Shanlin Yang;Shanlin Yang

  • Understanding household energy consumption behavior: The contribution of energy big data analytics

    Kaile Zhou;Shanlin Yang

  • Optimal load dispatch of community microgrid with deep learning based solar power and load forecasting

    Lulu Wen;Kaile Zhou;Kaile Zhou;Shanlin Yang;Xinhui Lu

  • Energy Internet: The business perspective

    Kaile Zhou;Shanlin Yang;Zhen Shao

  • Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies

    Zhifeng Guo;Kaile Zhou;Chi Zhang;Xinhui Lu

  • A review of electric load classification in smart grid environment

    Kai-le Zhou;Shan-lin Yang;Chao Shen

  • A two-warehouse inventory model for items with stock-level-dependent demand rate

    Yong-Wu Zhou;Shan-Lin Yang

  • Operating room planning and surgical case scheduling: a review of literature

    Shuwan Zhu;Shuwan Zhu;Wenjuan Fan;Wenjuan Fan;Shanlin Yang;Shanlin Yang;Jun Pei;Jun Pei;Jun Pei

  • Two-echelon supply chain models: Considering duopolistic retailers’ different competitive behaviors

    Shan-Lin Yang;Yong-Wu Zhou

  • Load demand forecasting of residential buildings using a deep learning model

    Lulu Wen;Kaile Zhou;Shanlin Yang

  • An improved boosting based on feature selection for corporate bankruptcy prediction

    Gang Wang;Jian Ma;Shanlin Yang

  • A group evidential reasoning approach based on expert reliability

    Chao Fu;Chao Fu;Jian-Bo Yang;Shan-Lin Yang;Shan-Lin Yang

  • A deep learning model for short-term power load and probability density forecasting

    Zhifeng Guo;Kaile Zhou;Kaile Zhou;Xiaoling Zhang;Shanlin Yang

  • Compression of smart meter big data: A survey

    Lulu Wen;Kaile Zhou;Shanlin Yang;Lanlan Li

  • Multi-objective optimal load dispatch of microgrid with stochastic access of electric vehicles

    Xinhui Lu;Xinhui Lu;Kaile Zhou;Kaile Zhou;Kaile Zhou;Shanlin Yang;Shanlin Yang;Huizhou Liu

  • Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment

    Yanni Jiang;Kaile Zhou;Xinhui Lu;Shanlin Yang

  • The group consensus based evidential reasoning approach for multiple attributive group decision analysis

    Chao Fu;Chao Fu;Shan-Lin Yang;Shan-Lin Yang

  • Combining QoS prediction and customer satisfaction estimation to solve cloud service trustworthiness evaluation problems

    Shuai Ding;Shanlin Yang;Youtao Zhang;Changyong Liang

  • Household monthly electricity consumption pattern mining: A fuzzy clustering-based model and a case study

    Kaile Zhou;Kaile Zhou;Shanlin Yang;Shanlin Yang;Zhen Shao

Frequent Co-Authors

Chi Zhang
Chi Zhang Hohai University

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