World's Best Scientists 2026 revealed!
Award Badge
Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
36
Citations
7937
World Ranking
785
National Ranking
42

Computer Science

D-Index
41
Citations
8837
World Ranking
8709
National Ranking
526

Cao Xiao 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 Cao Xiao 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: 136 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Cao Xiao 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 Cao Xiao 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Cao Xiao is a researcher affiliated with General Electric (United Kingdom) based in the United Kingdom. Their primary field of study is Computer Science, with a significant number of publications centered on Artificial Intelligence, molecular biology, computational theory and mathematics, materials chemistry, and radiology, nuclear medicine, and imaging.

The scientist's work spans several key topics within the intersection of technology and biomedical research. These include:

  • Machine Learning in Healthcare
  • Computational Drug Discovery Methods
  • Topic Modeling
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Materials Science
  • Artificial Intelligence in Healthcare and Education
  • Artificial Intelligence in Healthcare

Cao Xiao has contributed to numerous publications, with frequent appearances in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Patterns
  • Bioinformatics
  • Journal of the American Medical Informatics Association

Among recent papers associated with their research activity are:

  • MolTrans: Molecular Interaction Transformer for drug-target interaction prediction, 2020, Bioinformatics
  • Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review, 2020, Computers in Biology and Medicine
  • DeepPurpose: a deep learning library for drug-target interaction prediction, 2020, Bioinformatics
  • Artificial intelligence foundation for therapeutic science, 2022, Nature Chemical Biology
  • SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization, 2021, Bioinformatics

Throughout their research career, Cao Xiao has collaborated frequently with other scientists, including:

  • Jimeng Sun
  • Lucas M. Glass
  • Tianfan Fu
  • Kexin Huang
  • Brandon Theodorou

Best Publications

  • FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

    Jie Chen;Tengfei Ma;Cao Xiao

  • Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review.

    Cao Xiao;Edward Choi;Jimeng Sun

  • Patient Subtyping via Time-Aware LSTM Networks

    Inci M. Baytas;Cao Xiao;Xi Zhang;Fei Wang

  • MolTrans: Molecular interaction transformer for drug target interaction prediction

    Kexin Huang;Cao Xiao;Lucas M Glass;Jimeng Sun

  • Opportunities and challenges of deep learning methods for electrocardiogram data: A systematic review.

    Shenda Hong;Yuxi Zhou;Junyuan Shang;Cao Xiao

  • DeepPurpose: a deep learning library for drug-target interaction prediction.

    Kexin Huang;Tianfan Fu;Lucas M Glass;Marinka Zitnik

  • Pre-training of Graph Augmented Transformers for Medication Recommendation

    Junyuan Shang;Tengfei Ma;Cao Xiao;Jimeng Sun

  • GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

    Junyuan Shang;Cao Xiao;Tengfei Ma;Hongyan Li

  • Detecting Clusters of Fake Accounts in Online Social Networks

    Cao Xiao;David Mandell Freeman;Theodore Hwa

  • Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders

    Tengfei Ma;Cao Xiao;Jiayu Zhou;Fei Wang

  • MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare

    Edward Choi;Cao Xiao;Walter F. Stewart;Jimeng Sun

  • HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records

    Junyu Luo;Muchao Ye;Cao Xiao;Fenglong Ma

  • Data-Driven Subtyping of Parkinson's Disease Using Longitudinal Clinical Records: A Cohort Study.

    Xi Zhang;Jingyuan Chou;Jian Liang;Cao Xiao

  • SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization.

    Yue Yu;Kexin Huang;Chao Zhang;Lucas M Glass

  • Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

    Kexin Huang;Tianfan Fu;Wenhao Gao;Yue Zhao

  • CASTER: Predicting Drug Interactions with Chemical Substructure Representation

    Kexin Huang;Cao Xiao;Trong Nghia Hoang;Lucas M. Glass

  • An RNN Architecture with Dynamic Temporal Matching for Personalized Predictions of Parkinson's Disease.

    Chao Che;Cao Xiao;Jian Liang;Bo Jin

  • Readmission prediction via deep contextual embedding of clinical concepts.

    Cao Xiao;Tengfei Ma;Adji Bousso Dieng;David Meir Blei

  • SkipGNN: predicting molecular interactions with skip-graph networks.

    Kexin Huang;Cao Xiao;Lucas M. Glass;Marinka Zitnik

  • STAN: spatio-temporal attention network for pandemic prediction using real-world evidence.

    Junyi Gao;Rakshith Sharma;Cheng Qian;Lucas M Glass

  • Unsupervised Sequential Outlier Detection With Deep Architectures

    Weining Lu;Yu Cheng;Cao Xiao;Shiyu Chang

  • Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders

    Tengfei Ma;Jie Chen;Cao Xiao

Frequent Co-Authors

Jimeng Sun
Jimeng Sun University of Illinois at Urbana-Champaign
Fenglong Ma
Fenglong Ma Pennsylvania State University
M. Brandon Westover
M. Brandon Westover Harvard University
Marinka Zitnik
Marinka Zitnik Harvard University
Jiayu Zhou
Jiayu Zhou Michigan State University
Wanpracha Art Chaovalitwongse
Wanpracha Art Chaovalitwongse University of Arkansas at Fayetteville
Nicholas D. Sidiropoulos
Nicholas D. Sidiropoulos University of Virginia
Justin Romberg
Justin Romberg Georgia Institute of Technology
Jure Leskovec
Jure Leskovec Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

The field of computer science offers a variety of specialized online degree options in the USA. Students should prioritize enrolling in online universities that are accredited to ensure a recognized and respected qualification.

For those interested in the creative side of technology, pursuing a game development online degree can lead to exciting roles in the fast‐growing video game industry. Alternatively, the demand for digital security experts continues to rise, making a cyber security degree online a strong pathway to high-paying careers.

Computer science skills are also valuable in fields like construction management, where technology is driving industry innovation. Those interested in combining tech expertise with leadership should research online construction management degree cost and program options.

Exploring these related programs can help learners discover the best online degree to match their career interests and goals in the digital age.

Best Scientists Citing Cao Xiao

Trending Scientists

Recently Published Articles