World's Best Scientists 2026 revealed!
Aleksander Madry

Aleksander Madry

D-Index & Metrics

Computer Science

D-Index
51
Citations
10220
World Ranking
5348
National Ranking
2450

Aleksander Madry 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 Aleksander Madry 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: 94 publications — 7th percentile

7% of scientists in this discipline score the same or lower.

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

Aleksander Madry 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 Aleksander Madry 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: 51 D-Index — 63rd percentile

63% 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

  • 2016 - Fellow of Alfred P. Sloan Foundation

Overview

Aleksander Madry is affiliated with MIT in the United States, specializing primarily in the field of Computer Science. Their research centers on artificial intelligence, with a focus on adversarial robustness in machine learning. Their body of work spans multiple related topics including domain adaptation and few-shot learning, machine learning and data classification, advanced neural network applications, anomaly detection techniques and applications, COVID-19 diagnosis using AI, and advanced malware detection techniques.

The scientist has contributed extensively to scholarly publications, with a predominant presence in the venue arXiv (Cornell University), accounting for 47 of their works. Other publication venues include the Dagstuhl Research Online Publication Server, IEEE Transactions on Pattern Analysis and Machine Intelligence, Nature Neuroscience, and the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Among recent papers authored or co-authored by Aleksander Madry are:

  • On Assessing ML Model Robustness: A Methodological Framework (Academic Track), 2025, Dagstuhl Research Online Publication Server
  • Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • On Adaptive Attacks to Adversarial Example Defenses, 2020, arXiv (Cornell University)
  • Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO, 2020, arXiv (Cornell University)
  • Do Adversarially Robust ImageNet Models Transfer Better?, 2020, arXiv (Cornell University)

Frequent collaborators include:

  • Andrew Ilyas
  • Logan Engstrom
  • Hadi Salman
  • Guillaume Leclerc
  • Dimitris Tsipras

Aleksander Madry's primary subfields of study reflect the breadth of interests within artificial intelligence, including computer vision and pattern recognition, radiology, nuclear medicine and imaging, signal processing, and cognitive neuroscience.

The scientist received the award of Fellow of Alfred P. Sloan Foundation in 2016.

Best Publications

  • Robustness May Be at Odds with Accuracy

    Dimitris Tsipras;Shibani Santurkar;Logan Engstrom;Alexander Turner

  • Adversarial Examples Are Not Bugs, They Are Features

    Andrew Ilyas;Shibani Santurkar;Dimitris Tsipras;Logan Engstrom

  • On Evaluating Adversarial Robustness

    Nicholas Carlini;Anish Athalye;Nicolas Papernot;Wieland Brendel

  • On Adaptive Attacks to Adversarial Example Defenses

    Florian Tramer;Nicholas Carlini;Wieland Brendel;Aleksander Madry

  • Adversarially Robust Generalization Requires More Data

    Ludwig Schmidt;Shibani Santurkar;Dimitris Tsipras;Kunal Talwar

  • Spectral Signatures in Backdoor Attacks

    Brandon Tran;Jerry Li;Aleksander Madry

  • Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs

    Paul Christiano;Jonathan A. Kelner;Aleksander Madry;Daniel A. Spielman

  • A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations

    Logan Engstrom;Brandon Tran;Dimitris Tsipras;Ludwig Schmidt

  • Exploring the Landscape of Spatial Robustness

    Logan G. Engstrom;Brandon Tran;Dimitris Tsipras;Ludwig Schmidt

  • Prior convictions: Black-box adversarial attacks with bandits and priors

    Andrew. Ilyas;Logan G. Engstrom;Aleksander Madry

  • Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses.

    Micah Goldblum;Dimitris Tsipras;Chulin Xie;Xinyun Chen

  • Navigating Central Path with Electrical Flows: From Flows to Matchings, and Back

    Aleksander Madry

  • A Polylogarithmic-Competitive Algorithm for the k-Server Problem

    Nikhil Bansal;Niv Buchbinder;Aleksander Madry;Joseph (Seffi) Naor

  • How Does Batch Normalization Help Optimization

    Shibani Santurkar;Dimitris Tsipras;Andrew Ilyas;Aleksander Madry

  • Do Adversarially Robust ImageNet Models Transfer Better

    Hadi Salman;Andrew Ilyas;Logan Engstrom;Ashish Kapoor

  • Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

    Logan Engstrom;Andrew Ilyas;Shibani Santurkar;Dimitris Tsipras

  • Noise or Signal: The Role of Image Backgrounds in Object Recognition

    Kai Yuanqing Xiao;Logan Engstrom;Andrew Ilyas;Aleksander Madry

  • Clean-Label Backdoor Attacks

    Alexander Turner;Dimitris Tsipras;Aleksander Madry

  • Implementation Matters in Deep RL: A Case Study on PPO and TRPO

    Logan Engstrom;Andrew Ilyas;Shibani Santurkar;Dimitris Tsipras

  • Adversarial Robustness as a Prior for Learned Representations

    Logan Engstrom;Andrew Ilyas;Shibani Santurkar;Dimitris Tsipras

  • Image Synthesis with a Single (Robust) Classifier

    Shibani Santurkar;Andrew Ilyas;Dimitris Tsipras;Logan Engstrom

  • Label-Consistent Backdoor Attacks

    Alexander Turner;Dimitris Tsipras;Aleksander Madry

  • An O(log n/log log n)-approximation algorithm for the asymmetric traveling salesman problem

    Arash Asadpour;Michel X. Goemans;Aleksander Madry;Shayan Oveis Gharan

Frequent Co-Authors

Ashish Kapoor
Ashish Kapoor Microsoft (United States)
Nicholas Carlini
Nicholas Carlini Google (United States)
Niv Buchbinder
Niv Buchbinder Tel Aviv University
Gary L. Miller
Gary L. Miller Carnegie Mellon University
Nikhil Bansal
Nikhil Bansal University of Michigan–Ann Arbor
Richard Peng
Richard Peng Carnegie Mellon University
Daniel A. Spielman
Daniel A. Spielman Yale University
Scott Shenker
Scott Shenker University of California, Berkeley

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