World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
8143
World Ranking
7962
National Ranking
3430

Junfeng 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 Junfeng 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: 93 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Junfeng 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 Junfeng 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: 43 D-Index — 46th percentile

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

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

Overview

Junfeng Yang is affiliated with Columbia University in the United States. Their research predominantly lies within the field of Computer Science, with a focus on several specialized subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications, and Electrical and Electronic Engineering.

The main topics covered in their research include:

  • Adversarial Robustness in Machine Learning
  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Software Engineering Research
  • Advanced Malware Detection Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Security and Verification in Computing

Junfeng Yang has contributed to various publication venues, with the most frequent being:

  • arXiv (Cornell University)
  • Sustainability
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Access
  • IEEE Internet of Things Journal

The scientist's recent papers include:

  • Full Reference Image Quality Assessment by Considering Intra-Block Structure and Inter-Block Texture, 2020, IEEE Access
  • Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity, 2020, arXiv (Cornell University)
  • Adversarial Attacks are Reversible with Natural Supervision, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Multitask Learning Strengthens Adversarial Robustness, 2020, arXiv (Cornell University)
  • Performance Analysis of Delay Distribution and Packet Loss Ratio for Body-to-Body Networks, 2021, IEEE Internet of Things Journal

Frequent coauthors collaborating with Junfeng Yang include:

  • Chengzhi Mao
  • Baishakhi Ray
  • Carl Vondrick
  • Suman Jana
  • Amogh Gupta

In addition to journal and conference papers, Junfeng Yang has contributed to book publications, including a work published by Springer Nature titled Resilience and Future of Smart Learning in 2022.

Best Publications

  • DeepXplore: Automated Whitebox Testing of Deep Learning Systems

    Kexin Pei;Yinzhi Cao;Junfeng Yang;Suman Jana

  • An empirical study of operating systems errors

    Andy Chou;Junfeng Yang;Benjamin Chelf;Seth Hallem

  • Towards Making Systems Forget with Machine Unlearning

    Yinzhi Cao;Junfeng Yang

  • Using model checking to find serious file system errors

    Junfeng Yang;Paul Twohey;Dawson Engler;Madanlal Musuvathi

  • Formal Security Analysis of Neural Networks using Symbolic Intervals

    Shiqi Wang;Kexin Pei;Justin Whitehouse;Junfeng Yang

  • MODIST: transparent model checking of unmodified distributed systems

    Junfeng Yang;Tisheng Chen;Ming Wu;Zhilei Xu

  • Efficient Formal Safety Analysis of Neural Networks

    Shiqi Wang;Kexin Pei;Justin Whitehouse;Junfeng Yang

  • EXPLODE: a lightweight, general system for finding serious storage system errors

    Junfeng Yang;Can Sar;Dawson Engler

  • NEUZZ: Efficient Fuzzing with Neural Program Smoothing

    Dongdong She;Kexin Pei;Dave Epstein;Junfeng Yang

  • Correlation exploitation in error ranking

    Ted Kremenek;Ken Ashcraft;Junfeng Yang;Dawson Engler

  • Automatically generating malicious disks using symbolic execution

    Junfeng Yang;Can Sar;P. Twohey;C. Cadar

  • Stable deterministic multithreading through schedule memoization

    Heming Cui;Jingyue Wu;Chia-Che Tsai;Junfeng Yang

  • Efficiently, effectively detecting mobile app bugs with AppDoctor

    Gang Hu;Xinhao Yuan;Yang Tang;Junfeng Yang

  • DeepXplore: automated whitebox testing of deep learning systems

    Kexin Pei;Yinzhi Cao;Junfeng Yang;Suman Jana

  • Practical software model checking via dynamic interface reduction

    Huayang Guo;Ming Wu;Lidong Zhou;Gang Hu

  • Metric Learning for Adversarial Robustness

    Chengzhi Mao;Ziyuan Zhong;Junfeng Yang;Carl Vondrick

  • Shuffler: fast and deployable continuous code re-randomization

    David Williams-King;Graham Gobieski;Kent Williams-King;James P. Blake

  • Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems

    Kexin Pei;Yinzhi Cao;Junfeng Yang;Suman Jana

  • Fingerprinting event logs for system management troubleshooting

    Rina Panigrahy;Chad Verbowski;Yinglian Xie;Junfeng Yang

  • Parrot: a practical runtime for deterministic, stable, and reliable threads

    Heming Cui;Jiri Simsa;Yi-Hong Lin;Hao Li

  • Efficient deterministic multithreading through schedule relaxation

    Heming Cui;Jingyue Wu;John Gallagher;Huayang Guo

Frequent Co-Authors

Suman Jana
Suman Jana Columbia University
Baishakhi Ray
Baishakhi Ray Columbia University
Dawson Engler
Dawson Engler Stanford University
Carl Vondrick
Carl Vondrick Columbia University
Lidong Zhou
Lidong Zhou Microsoft (United States)
Hao Wang
Hao Wang Swinburne University of Technology
Angelos D. Keromytis
Angelos D. Keromytis Georgia Institute of Technology
Salvatore J. Stolfo
Salvatore J. Stolfo Columbia University
Jason Nieh
Jason Nieh Columbia University
Lintao Zhang
Lintao Zhang Microsoft (United States)

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