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Computer Science

D-Index
37
Citations
8492
World Ranking
10527
National Ranking
4411

Alina Oprea 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 Alina Oprea 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: 118 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Alina Oprea 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 Alina Oprea 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Alina Oprea is a researcher affiliated with Northeastern University in the United States. Their primary field of study is Computer Science, with a focus on Artificial Intelligence, Computer Networks and Communications, and Signal Processing. Additional areas of work include Sociology and Political Science as well as Information Systems.

The main research topics addressed by Oprea include:

  • Adversarial Robustness in Machine Learning
  • Network Security and Intrusion Detection
  • Privacy-Preserving Technologies in Data
  • Anomaly Detection Techniques and Applications
  • Advanced Malware Detection Techniques
  • Internet Traffic Analysis and Secure E-voting
  • Cryptography and Data Security

Oprea has an extensive publication record with a total of 111 contributions in Computer Science. Of these, 78 concern Artificial Intelligence specifically. Their publications often appear in venues such as arXiv (Cornell University), ACM Transactions on Privacy and Security, Proceedings on Privacy Enhancing Technologies, IEEE Security & Privacy, and ACM Computing Surveys.

Recent notable papers authored or coauthored by Oprea include:

  • "Extracting Training Data from Large Language Models," 2020, arXiv (Cornell University)
  • "Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning," 2023, ACM Computing Surveys
  • "Auditing Differentially Private Machine Learning: How Private is Private SGD?" 2020, arXiv (Cornell University)
  • "Explanation-Guided Backdoor Poisoning Attacks Against Malware Classifiers," 2020, arXiv (Cornell University)
  • "FENCE: Feasible Evasion Attacks on Neural Networks in Constrained Environments," 2022, ACM Transactions on Privacy and Security

Collaborative work is an important aspect of Oprea's research output. Frequent coauthors include:

  • Simona Boboila
  • Matthew Jagielski
  • Jonathan Ullman
  • Giorgio Severi
  • Tina Eliassi-Rad

Best Publications

  • HAIL: a high-availability and integrity layer for cloud storage

    Kevin D. Bowers;Ari Juels;Alina Oprea

  • Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

    Matthew Jagielski;Alina Oprea;Battista Biggio;Chang Liu

  • Proofs of retrievability: theory and implementation

    Kevin D. Bowers;Ari Juels;Alina Oprea

  • HomeAlone: Co-residency Detection in the Cloud via Side-Channel Analysis

    Yinqian Zhang;Ari Juels;Alina Oprea;Michael K. Reiter

  • Extracting Training Data from Large Language Models

    Nicholas Carlini;Florian Tramèr;Eric Wallace;Matthew Jagielski

  • Beehive: large-scale log analysis for detecting suspicious activity in enterprise networks

    Ting-Fang Yen;Alina Oprea;Kaan Onarlioglu;Todd Leetham

  • FlipIt: The Game of Stealthy Takeover

    Marten Dijk;Ari Juels;Alina Oprea;Ronald L. Rivest

  • Iris: a scalable cloud file system with efficient integrity checks

    Emil Stefanov;Marten van Dijk;Ari Juels;Alina Oprea

  • Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks

    Ambra Demontis;Marco Melis;Maura Pintor;Matthew Jagielski

  • Detection of Early-Stage Enterprise Infection by Mining Large-Scale Log Data

    Alina Oprea;Zhou Li;Ting-Fang Yen;Sang H. Chin

  • New approaches to security and availability for cloud data

    Ari Juels;Alina Oprea

  • Detection of malicious web activity in enterprise computer networks

    Alina M. Oprea;Zhou Li;Robin Norris;Kevin D. Bowers

  • Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning

    Unknown

  • Space-Efficient Block Storage Integrity.

    Alina Oprea;Michael K. Reiter

  • How to tell if your cloud files are vulnerable to drive crashes

    Kevin D. Bowers;Marten van Dijk;Ari Juels;Alina Oprea

  • Scalable cloud file system with efficient integrity checks

    Emil P. Stefanov;Marten E. Van Dijk;Alina M. Oprea;Ari Juels

  • Robust Linear Regression Against Training Data Poisoning

    Chang Liu;Bo Li;Yevgeniy Vorobeychik;Alina Oprea

  • Securing a remote terminal application with a mobile trusted device

    A. Oprea;D. Balfanz;G. Durfee;D.K. Smetters

  • Hourglass schemes: how to prove that cloud files are encrypted

    Marten van Dijk;Ari Juels;Alina Oprea;Ronald L. Rivest

  • An Epidemiological Study of Malware Encounters in a Large Enterprise

    Ting-Fang Yen;Victor Heorhiadi;Alina Oprea;Michael K. Reiter

  • Auditing Differentially Private Machine Learning: How Private is Private SGD?

    Matthew Jagielski;Jonathan R. Ullman;Alina Oprea

  • Differentially Private Fair Learning

    Matthew Jagielski;Michael J. Kearns;Jieming Mao;Alina Oprea

  • Iris: A Scalable Cloud File System with Efficient Integrity Checks.

    Emil Stefanov;Marten van Dijk;Alina Oprea;Ari Juels

Frequent Co-Authors

Ari Juels
Ari Juels Cornell University
Marten van Dijk
Marten van Dijk University of Connecticut
Michael K. Reiter
Michael K. Reiter Duke University
Cristina Nita-Rotaru
Cristina Nita-Rotaru Northeastern University
Dawn Song
Dawn Song University of California, Berkeley
Battista Biggio
Battista Biggio University of Cagliari
Christian Cachin
Christian Cachin University of Bern
Michael Backes
Michael Backes University of Oxford
William Robertson
William Robertson Northeastern University

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