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Jun Zhu

D-Index & Metrics

Biology and Biochemistry

D-Index
84
Citations
45641
World Ranking
3229
National Ranking
1634

Jun Zhu publication distribution in Biology and Biochemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Biology and Biochemistry in 2026. The highlighted bar marks where Jun Zhu sits on this spectrum.

47–56 publications: 8 scientists 57–66 publications: 35 scientists 67–76 publications: 106 scientists 77–86 publications: 231 scientists 87–96 publications: 414 scientists 97–106 publications: 546 scientists 107–116 publications: 704 scientists 117–126 publications: 849 scientists 127–136 publications: 980 scientists 137–146 publications: 942 scientists 147–156 publications: 969 scientists 157–166 publications: 950 scientists 167–176 publications: 951 scientists 177–186 publications: 915 scientists 187–196 publications: 787 scientists 197–206 publications: 841 scientists 207–216 publications: 735 scientists 217–226 publications: 709 scientists 227–236 publications: 651 scientists 237–246 publications: 605 scientists 247–256 publications: 510 scientists 257–266 publications: 524 scientists 267–276 publications: 434 scientists 277–286 publications: 418 scientists 287–296 publications: 350 scientists 297–306 publications: 363 scientists 307–316 publications: 315 scientists 317–326 publications: 296 scientists 327–336 publications: 261 scientists 337–346 publications: 240 scientists 347–356 publications: 219 scientists 357–366 publications: 197 scientists 367–376 publications: 154 scientists 377–386 publications: 161 scientists 387–396 publications: 155 scientists 397–406 publications: 145 scientists 407–416 publications: 124 scientists 417–426 publications: 112 scientists 427–436 publications: 132 scientists 437–446 publications: 116 scientists 447–456 publications: 99 scientists 457–466 publications: 81 scientists 467–476 publications: 91 scientists 477–486 publications: 80 scientists 487–496 publications: 80 scientists 497–506 publications: 60 scientists 507–516 publications: 36 scientists 517–526 publications: 46 scientists 527–536 publications: 54 scientists 537–546 publications: 44 scientists 547–556 publications: 43 scientists 557–566 publications: 43 scientists 567–576 publications: 42 scientists 577–586 publications: 25 scientists 587–596 publications: 34 scientists 597–606 publications: 23 scientists 607–616 publications: 33 scientists 617–626 publications: 31 scientists 627–636 publications: 27 scientists 637–646 publications: 25 scientists 647–656 publications: 28 scientists 657–666 publications: 34 scientists 667–676 publications: 18 scientists 677–686 publications: 16 scientists 687–696 publications: 10 scientists 697–706 publications: 12 scientists 707–716 publications: 21 scientists 717–726 publications: 12 scientists 727–736 publications: 12 scientists 737–746 publications: 10 scientists 747–756 publications: 7 scientists 757–766 publications: 13 scientists 767–776 publications: 15 scientists 777–786 publications: 13 scientists 787–796 publications: 9 scientists 797–806 publications: 9 scientists 807–816 publications: 7 scientists 817–826 publications: 4 scientists 827–836 publications: 9 scientists 837–846 publications: 7 scientists 847–856 publications: 3 scientists 857–866 publications: 5 scientists 867–876 publications: 5 scientists 877–886 publications: 11 scientists 887–896 publications: 3 scientists 897–906 publications: 4 scientists 907–916 publications: 7 scientists 917–926 publications: 5 scientists 927–936 publications: 6 scientists 937–946 publications: 6 scientists 947–956 publications: 3 scientists 957–966 publications: 7 scientists 967–976 publications: 2 scientists 977–986 publications: 2 scientists 987–996 publications: 1 scientists 997–1,006 publications: 5 scientists 1,007–1,016 publications: 2 scientists 1,017–1,026 publications: 2 scientists 1,027 publications: 1 scientists 1,028+ publications: 100 scientists
47 publications 1,028+

This scientist: 247 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,028 publications or more.

Jun Zhu D-index placement in Biology and Biochemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Biology and Biochemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Jun Zhu sits on this spectrum.

40–41 D-Index: 80 scientists 42–43 D-Index: 183 scientists 44–45 D-Index: 317 scientists 46–47 D-Index: 504 scientists 48–49 D-Index: 718 scientists 50–51 D-Index: 900 scientists 52–53 D-Index: 1,026 scientists 54–55 D-Index: 1,150 scientists 56–57 D-Index: 1,236 scientists 58–59 D-Index: 1,253 scientists 60–61 D-Index: 1,163 scientists 62–63 D-Index: 1,131 scientists 64–65 D-Index: 1,032 scientists 66–67 D-Index: 897 scientists 68–69 D-Index: 814 scientists 70–71 D-Index: 715 scientists 72–73 D-Index: 709 scientists 74–75 D-Index: 596 scientists 76–77 D-Index: 512 scientists 78–79 D-Index: 473 scientists 80–81 D-Index: 412 scientists 82–83 D-Index: 373 scientists 84–85 D-Index: 358 scientists 86–87 D-Index: 285 scientists 88–89 D-Index: 273 scientists 90–91 D-Index: 227 scientists 92–93 D-Index: 208 scientists 94–95 D-Index: 193 scientists 96–97 D-Index: 153 scientists 98–99 D-Index: 157 scientists 100–101 D-Index: 148 scientists 102–103 D-Index: 120 scientists 104–105 D-Index: 113 scientists 106–107 D-Index: 100 scientists 108–109 D-Index: 86 scientists 110–111 D-Index: 67 scientists 112–113 D-Index: 72 scientists 114–115 D-Index: 73 scientists 116–117 D-Index: 64 scientists 118–119 D-Index: 53 scientists 120–121 D-Index: 60 scientists 122–123 D-Index: 54 scientists 124–125 D-Index: 43 scientists 126–127 D-Index: 38 scientists 128–129 D-Index: 49 scientists 130–131 D-Index: 26 scientists 132–133 D-Index: 18 scientists 134–135 D-Index: 23 scientists 136–137 D-Index: 32 scientists 138–139 D-Index: 32 scientists 140–141 D-Index: 27 scientists 142–143 D-Index: 19 scientists 144–145 D-Index: 22 scientists 146–147 D-Index: 12 scientists 148–149 D-Index: 16 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 10 scientists 154–155 D-Index: 13 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 9 scientists 162–163 D-Index: 13 scientists 164–165 D-Index: 4 scientists 166 D-Index: 4 scientists 167+ D-Index: 98 scientists
40 D-Index 167+

This scientist: 84 D-Index — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 167 D-Index or more.

Overview

Jun Zhu is affiliated with the Icahn School of Medicine at Mount Sinai in the United States. Their research primarily lies within the field of computer science, with a focus on artificial intelligence. Their work extensively covers subfields such as artificial intelligence, computer vision and pattern recognition, statistical and nonlinear physics, signal processing, and control and systems engineering.

The main topics of Jun Zhu's research include:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Domain Adaptation and Few-Shot Learning
  • Model Reduction and Neural Networks
  • Generative Adversarial Networks and Image Synthesis
  • Multimodal Machine Learning Applications
  • Advanced Neural Network Applications

Jun Zhu has a significant publication record with frequent contributions to notable venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Nature Machine Intelligence

Examples of recent papers featuring Jun Zhu's work are:

  • "Pre-trained models: Past, present and future" (2021) published in AI Open
  • "A Comprehensive Survey of Continual Learning: Theory, Method and Application" (2024) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (2022) published in arXiv (Cornell University)
  • "Towards a new generation of artificial intelligence in China" (2020) published in Nature Machine Intelligence
  • "Tianshou: a Highly Modularized Deep Reinforcement Learning Library" (2021) published in arXiv (Cornell University)

Jun Zhu frequently collaborates with other researchers, including:

  • Hang Su
  • Yinpeng Dong
  • Xiao Yang
  • Chongxuan Li
  • Tianyu Pang

Best Publications

  • The Genotype-Tissue Expression (GTEx) project

    John Lonsdale;Jeffrey Thomas;Mike Salvatore;Rebecca Phillips

  • The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

    Kristin G. Ardlie;David S. Deluca;Ayellet V. Segrè

  • SPIDER AND WEB : PROCESSING AND VISUALIZATION OF IMAGES IN 3D ELECTRON MICROSCOPY AND RELATED FIELDS

    Joachim Frank;Michael Radermacher;Michael Radermacher;Pawel A Penczek;Jun Zhu;Jun Zhu

  • Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease

    Bin Zhang;Chris Gaiteri;Liviu Gabriel Bodea;Zhi Wang

  • Genetics of gene expression and its effect on disease

    Valur Emilsson;Gudmar Thorleifsson;Bin Zhang;Amy S. Leonardson

  • An integrative genomics approach to infer causal associations between gene expression and disease

    Eric E Schadt;John Lamb;Xia Yang;Jun Zhu

  • Correction: Corrigendum: Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases

    Jialiang Yang;Tao Huang;Francesca Petralia;Quan Long

  • Gene expression elucidates functional impact of polygenic risk for schizophrenia

    Menachem Fromer;Panos Roussos;Solveig K. Sieberts;Jessica S. Johnson

  • Mapping the Genetic Architecture of Gene Expression in Human Liver

    Eric E. Schadt;Cliona Molony;Eugene Chudin;Ke-Ke Hao

  • Variations in DNA elucidate molecular networks that cause disease

    Yanqing Chen;Jun Zhu;Pek Yee Lum;Xia Yang

  • Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

    David J. Clark;Saravana M. Dhanasekaran;Francesca Petralia;Jianbo Pan

  • Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks.

    Jun Zhu;Bin Zhang;Erin N Smith;Erin N Smith;Becky Drees

  • Proteogenomic and metabolomic characterization of human glioblastoma

    Liang-Bo Wang;Alla Karpova;Marina A. Gritsenko;Jennifer E. Kyle

  • A model of protein synthesis based on cryo-electron microscopy of the E. coli ribosome

    Joachim Frank;Jun Zhu;Jun Zhu;Pawel A Penczek;Yanhong Li;Yanhong Li

  • Co-regulatory networks of human serum proteins link genetics to disease

    Valur Emilsson;Marjan Ilkov;John R. Lamb;Nancy Finkel

  • Reduced Retinoic Acid-Sensitivities of Nuclear Receptor Corepressor Binding to PML- and PLZF-RARα Underlie Molecular Pathogenesis and Treatment of Acute Promyelocytic Leukemia

    Fabien Guidez;Sarah Ivins;Sarah Ivins;Sarah Ivins;Jun Zhu;Jun Zhu;Jun Zhu;Mats Söderström;Mats Söderström;Mats Söderström

  • Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions.

    S K Sieberts;T M Perumal;M M Carrasquillo;M Allen

  • Validation of candidate causal genes for obesity that affect shared metabolic pathways and networks.

    Xia Yang;Joshua L Deignan;Hongxiu Qi;Jun Zhu

  • Cancer Cell Dependence on Unsaturated Fatty Acids Implicates Stearoyl-CoA Desaturase as a Target for Cancer Therapy

    Urvashi V. Roongta;Jonathan G. Pabalan;Xinyu Wang;Rolf-Peter Ryseck

  • The Genotype-Tissue Expression (GTEx) project

    John Lonsdale;Jeffrey Thomas;Mike Salvatore;Rebecca Phillips

Frequent Co-Authors

Eric E. Schadt
Eric E. Schadt Icahn School of Medicine at Mount Sinai
Bin Zhang
Bin Zhang Icahn School of Medicine at Mount Sinai
Xia Yang
Xia Yang University of California, Los Angeles
William Oh
William Oh Icahn School of Medicine at Mount Sinai
Ke Hao
Ke Hao Icahn School of Medicine at Mount Sinai
Robert Sebra
Robert Sebra Icahn School of Medicine at Mount Sinai
Mayte Suárez-Fariñas
Mayte Suárez-Fariñas Icahn School of Medicine at Mount Sinai
Pei Wang
Pei Wang Icahn School of Medicine at Mount Sinai
Aldons J. Lusis
Aldons J. Lusis University of California, Los Angeles
Nina Bhardwaj
Nina Bhardwaj Icahn School of Medicine at Mount Sinai

External Links

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Related Online Degrees & Career Pathways

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Best Scientists Citing Jun Zhu

Kari Stefansson

Kari Stefansson

deCODE Genetics (Iceland)

Publications: 200

Joachim Frank

Joachim Frank

Columbia University

Publications: 199

Eric E. Schadt

Eric E. Schadt

Icahn School of Medicine at Mount Sinai

Publications: 175

André G. Uitterlinden

André G. Uitterlinden

Erasmus University Rotterdam

Publications: 146

Eric Boerwinkle

Eric Boerwinkle

The University of Texas Health Science Center at Houston

Publications: 139

Unnur Thorsteinsdottir

Unnur Thorsteinsdottir

deCODE Genetics (Iceland)

Publications: 138

Mark I. McCarthy

Mark I. McCarthy

Genentech

Publications: 137

Bruce M. Psaty

Bruce M. Psaty

University of Washington

Publications: 123

Jerome I. Rotter

Jerome I. Rotter

UCLA Medical Center

Publications: 119

Tonu Esko

Tonu Esko

University of Tartu

Publications: 112

Aarno Palotie

Aarno Palotie

University of Helsinki

Publications: 110

Andrew P. Morris

Andrew P. Morris

University of Liverpool

Publications: 108

Emmanouil T. Dermitzakis

Emmanouil T. Dermitzakis

University of Geneva

Publications: 108

Tim D. Spector

Tim D. Spector

King's College London

Publications: 107

Grant W. Montgomery

Grant W. Montgomery

University of Queensland

Publications: 106

Nicholas G. Martin

Nicholas G. Martin

QIMR Berghofer Medical Research Institute

Publications: 104

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