World's Best Scientists 2026 revealed!
Neil Zhenqiang Gong

Neil Zhenqiang Gong

D-Index & Metrics

Computer Science

D-Index
50
Citations
8969
World Ranking
5666
National Ranking
2579

Neil Zhenqiang Gong 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 Neil Zhenqiang Gong 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: 201 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Neil Zhenqiang Gong 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 Neil Zhenqiang Gong 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Neil Zhenqiang Gong is affiliated with Duke University in the United States. Their research primarily falls within the field of Computer Science, with a substantial focus on Artificial Intelligence. Additional subfields include Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Computer Networks and Communications.

Their academic work spans several main topics, notably Adversarial Robustness in Machine Learning, Privacy-Preserving Technologies in Data, Advanced Graph Neural Networks, Anomaly Detection Techniques and Applications, Digital Media Forensic Detection, Cryptography and Data Security, and Advanced Steganography and Watermarking Techniques.

Neil Zhenqiang Gong has published extensively in various venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 2022 ACM on Asia Conference on Computer and Communications Security
  • Proceedings on Privacy Enhancing Technologies
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Some of their recent papers are:

  • FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients, 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Provably Secure Federated Learning against Malicious Clients, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • BadEncoder: Backdoor Attacks to Pre-trained Encoders in Self-Supervised Learning, 2022, 2022 IEEE Symposium on Security and Privacy (SP)
  • Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • FLCert: Provably Secure Federated Learning Against Poisoning Attacks, 2022, IEEE Transactions on Information Forensics and Security

Frequent coauthors working with Neil Zhenqiang Gong include:

  • Jinyuan Jia
  • Xiaoyu Cao
  • Minghong Fang
  • Yuepeng Hu

The research contributions cover topics that include theoretical and practical aspects of federated learning security and robustness against model poisoning and backdoor attacks, as well as certifiable defenses in machine learning systems.

Best Publications

  • FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping.

    Xiaoyu Cao;Minghong Fang;Jia Liu;Neil Zhenqiang Gong

  • Stealing Hyperparameters in Machine Learning

    Binghui Wang;Neil Zhenqiang Gong

  • On the Feasibility of Internet-Scale Author Identification

    A. Narayanan;H. Paskov;N. Z. Gong;J. Bethencourt

  • Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

    Minghong Fang;Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

  • MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

    Jinyuan Jia;Ahmed Salem;Michael Backes;Yang Zhang

  • FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients

    Unknown

  • Evolution of social-attribute networks: measurements, modeling, and implications using google+

    Neil Zhenqiang Gong;Wenchang Xu;Ling Huang;Prateek Mittal

  • SybilBelief: A Semi-Supervised Learning Approach for Structure-Based Sybil Detection

    Neil Zhenqiang Gong;Mario Frank;Prateek Mittal

  • Joint Link Prediction and Attribute Inference Using a Social-Attribute Network

    Neil Zhenqiang Gong;Ameet Talwalkar;Lester Mackey;Ling Huang

  • Backdoor Attacks to Graph Neural Networks

    Zaixi Zhang;Jinyuan Jia;Binghui Wang;Neil Zhenqiang Gong

  • Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification

    Xiaoyu Cao;Neil Zhenqiang Gong

  • PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

    Unknown

  • TrustLLM: Trustworthiness in Large Language Models

    Unknown

  • Local Model Poisoning Attacks to Byzantine-Robust Federated Learning.

    Minghong Fang;Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

  • Attacking Graph-based Classification via Manipulating the Graph Structure

    Binghui Wang;Neil Zhenqiang Gong

  • Influence Function based Data Poisoning Attacks to Top-N Recommender Systems

    Minghong Fang;Neil Zhenqiang Gong;Jia Liu

  • Random Walk Based Fake Account Detection in Online Social Networks

    Jinyuan Jia;Binghui Wang;Neil Zhenqiang Gong

  • IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary

    Xiaoyu Cao;Jinyuan Jia;Neil Zhenqiang Gong

  • Personalized Mobile App Recommendation: Reconciling App Functionality and User Privacy Preference

    Bin Liu;Deguang Kong;Lei Cen;Neil Zhenqiang Gong

  • Attribute Inference Attacks in Online Social Networks

    Neil Zhenqiang Gong;Bin Liu

  • Poisoning Attacks to Graph-Based Recommender Systems

    Minghong Fang;Guolei Yang;Neil Zhenqiang Gong;Jia Liu

  • Poisoning Attacks to Graph-Based Recommender Systems

    Minghong Fang;Guolei Yang;Neil Zhenqiang Gong;Jia Liu

  • Fake Co-visitation Injection Attacks to Recommender Systems.

    Guolei Yang;Neil Zhenqiang Gong;Ying Cai

  • Practical Blind Membership Inference Attack via Differential Comparisons

    Bo Hui;Yuchen Yang;Haolin Yuan;Philippe Burlina

  • On Certifying Robustness against Backdoor Attacks via Randomized Smoothing

    Binghui Wang;Xiaoyu Cao;Jinyuan jia;Neil Zhenqiang Gong

  • Data Poisoning Attacks to Deep Learning Based Recommender Systems.

    Hai Huang;Jiaming Mu;Neil Zhenqiang Gong;Qi Li

Frequent Co-Authors

Dawn Song
Dawn Song University of California, Berkeley
Prateek Mittal
Prateek Mittal Princeton University
Hongxia Jin
Hongxia Jin Samsung (United States)
Ling Huang
Ling Huang Intel (United States)
Mathias Payer
Mathias Payer École Polytechnique Fédérale de Lausanne
Michael Backes
Michael Backes University of Oxford
Sanjeev R. Kulkarni
Sanjeev R. Kulkarni Princeton University
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Jingren Zhou
Jingren Zhou Alibaba Group (China)
Defu Lian
Defu Lian University of Science and Technology of China

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

Exploring computer science opens the door to multiple interdisciplinary opportunities and career pathways. Many students combine their computer science background with fields such as engineering, physics, or data science to broaden their skill set and marketability in the tech industry.

If affordability is a priority, you may consider programs such as the cheapest online master's mechanical engineering or the cheapest master in data science. Both fields—closely related to computer science—prepare graduates for roles in innovation and advanced technology.

For those interested in theoretical foundations, there are options like an online theoretical physics degree, which integrates computational and analytical skills sought after in research and academia.

Additionally, an online master’s in electrical engineering degree can lead to careers in robotics, embedded systems, and hardware design—fields that increasingly depend on computer science expertise.

Broadening your studies with these online degrees can enhance your career options and keep you competitive in today’s evolving technology landscape.

Best Scientists Citing Neil Zhenqiang Gong

Trending Scientists