World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9692
World Ranking
4388
National Ranking
2048

Oleg Sokolsky 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 Oleg Sokolsky 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: 339 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Oleg Sokolsky 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 Oleg Sokolsky 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Oleg Sokolsky is affiliated with the University of Pennsylvania in the United States and has a research focus spanning computer science and engineering disciplines. Their work contributes substantially to subfields such as artificial intelligence, software, control and systems engineering, signal processing, and computational theory and mathematics.

The main topics addressed by Sokolsky include adversarial robustness in machine learning, anomaly detection techniques and applications, fault detection and control systems, software reliability and analysis research, formal methods in verification, advanced malware detection techniques, and software testing and debugging techniques.

Prominent coauthors who have frequently collaborated with Sokolsky are:

  • Insup Lee
  • Ivan Ruchkin
  • James Weimer
  • Matthew Cleaveland
  • Pengyuan Lu

Oleg Sokolsky has frequently published in venues such as:

  • arXiv (Cornell University)
  • ACM Transactions on Embedded Computing Systems
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 American Control Conference (ACC)
  • ACM Computing Surveys

Recent papers authored or coauthored by Sokolsky include:

  • Real-time Attack-recovery for Cyber-physical Systems Using Linear-quadratic Regulator, 2021, ACM Transactions on Embedded Computing Systems
  • iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection, 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • Improving Neural Network Robustness via Persistency of Excitation, 2022, 2022 American Control Conference (ACC)
  • Detecting OODs as datapoints with High Uncertainty, 2021, arXiv (Cornell University)
  • Recovery from Adversarial Attacks in Cyber-physical Systems: Shallow, Deep, and Exploratory Works, 2024, ACM Computing Surveys

Sokolsky has also authored books published by Springer Science+Business Media, including Automated Technology for Verification and Analysis (2020) and NASA Formal Methods (2022).

Best Publications

  • Challenges and Research Directions in Medical Cyber–Physical Systems

    Insup Lee;O. Sokolsky;Sanjian Chen;J. Hatcliff

  • Java-MaC: A Run-Time Assurance Approach for Java Programs

    Moonzoo Kim;Mahesh Viswanathan;Sampath Kannan;Insup Lee

  • Robustness of Attack-Resilient State Estimators

    Miroslav Pajic;James Weimer;Nicola Bezzo;Paulo Tabuada

  • Java-MaC: A Run-time Assurance Tool for Java Programs

    Moonjoo Kim;Sampath Kannan;Insup Lee;Oleg Sokolsky

  • Runtime Assurance Based On Formal Specifications

    Insup Lee;Sampath Kannan;Moonjoo Kim;Oleg Sokolsky

  • Hierarchical modeling and analysis of embedded systems

    R. Alur;Thao Dang;J. Esposito;Yerang Hur

  • Medical cyber physical systems

    Insup Lee;Oleg Sokolsky

  • A Temporal Logic Based Theory of Test Coverage and Generation

    Hyoung Seok Hong;Insup Lee;Oleg Sokolsky;Hasan Ural

  • Formally specified monitoring of temporal properties

    Moonjoo Kim;M. Viswanathan;H. Ben-Abdallah;S. Kannan

  • Toward patient safety in closed-loop medical device systems

    David Arney;Miroslav Pajic;Julian M. Goldman;Insup Lee

  • Data flow testing as model checking

    Hyoung Seok Hong;Sung Deok Cha;Insup Lee;Oleg Sokolsky

  • Design and Implementation of Attack-Resilient Cyberphysical Systems: With a Focus on Attack-Resilient State Estimators

    Miroslav Pajic;James Weimer;Nicola Bezzo;Oleg Sokolsky

  • Hierarchical Hybrid Modeling of Embedded Systems

    Rajeev Alur;Thao Dang;Joel M. Esposito;Rafael B. Fierro

  • Model-Driven Safety Analysis of Closed-Loop Medical Systems

    Miroslav Pajic;Rahul Mangharam;Oleg Sokolsky;David Arney

  • Real-time multi-core virtual machine scheduling in xen

    Sisu Xi;Meng Xu;Chenyang Lu;Linh T. X. Phan

  • Verisim: formal analysis of network simulations

    K. Bhargavan;C.A. Gunter;Moonjoo Kim;Insup Lee

  • Weak Bisimulation for Probabilistic Systems

    Anna Philippou;Insup Lee;Oleg Sokolsky

  • Incremental Model Checking in the Modal Mu-Calculus

    Oleg Sokolsky;Scott A. Smolka

  • Schedulability analysis of AADL models

    Oleg Sokolsky;Insup Lee;Duncan Clarke

  • Specification-based testing with linear temporal logic

    L. Tan;O. Sokolsky;I. Lee

Frequent Co-Authors

Insup Lee
Insup Lee University of Pennsylvania
Sampath Kannan
Sampath Kannan University of Pennsylvania
Miroslav Pajic
Miroslav Pajic Duke University
George J. Pappas
George J. Pappas University of Pennsylvania
Mahesh Viswanathan
Mahesh Viswanathan University of Illinois at Urbana-Champaign
Scott A. Smolka
Scott A. Smolka Stony Brook University
Mats P. E. Heimdahl
Mats P. E. Heimdahl University of Minnesota
Rajeev Alur
Rajeev Alur University of Pennsylvania
Boon Thau Loo
Boon Thau Loo University of Pennsylvania
Chenyang Lu
Chenyang Lu Washington University in St. Louis

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