World's Best Scientists 2026 revealed!

Robert Moskovitch 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 Robert Moskovitch 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+

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

Robert Moskovitch 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 Robert Moskovitch 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+

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

Overview

Robert Moskovitch is affiliated with Columbia University in the United States and has contributed extensively to the field of computer science, with a particular focus on signal processing and artificial intelligence. Their research spans various subfields including information systems, computer networks and communications, and health information management.

The scientist has published a significant number of papers, covering prominent topics such as time series analysis and forecasting, data management and algorithms, data mining applications, machine learning in healthcare, music and audio processing, anomaly detection techniques, and artificial intelligence in healthcare.

Recent publications include:

  • "Decompiled APK based malicious code classification" (2020) in Future Generation Computer Systems
  • "Outcomes prediction in longitudinal data: Study designs evaluation, use case in ICU acquired sepsis" (2021) in Journal of Biomedical Informatics
  • "Complete Closed Time Intervals-Related Patterns Mining" (2021) in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Multivariate temporal data analysis - a review" (2021) in Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
  • "Temporal pattern-based malicious activity detection in SCADA systems" (2020) in Computers & Security

Their publication history shows a pattern of contributions to notable academic venues including the Journal of Biomedical Informatics, Future Generation Computer Systems, Proceedings of the AAAI Conference on Artificial Intelligence, Artificial Intelligence in Medicine, and PLoS ONE.

Robert Moskovitch has also contributed to book publications, with at least one title published through Springer Science+Business Media titled "Artificial Intelligence in Medicine" (2020).

Collaborative work is an important aspect of their research profile. Frequent co-authors include Nevo Itzhak, Szymon Jaroszewicz, Roni Mateless, Omer David Harel, and Paulo Saldanha, reflecting ongoing partnerships within their fields of study.

Main research fields and topics:

  • Computer Science
  • Signal Processing
  • Artificial Intelligence
  • Information Systems
  • Computer Networks and Communications
  • Health Information Management
  • Time Series Analysis and Forecasting
  • Data Management and Algorithms
  • Data Mining Algorithms and Applications
  • Machine Learning in Healthcare
  • Music and Audio Processing
  • Anomaly Detection Techniques and Applications
  • Artificial Intelligence in Healthcare

The scope of their research reflects interdisciplinary engagement across computational techniques, healthcare applications, and cybersecurity aspects, indicating a broad approach within computer science and its applied domains.

Best Publications

  • Detection of malicious code by applying machine learning classifiers on static features: A state-of-the-art survey

    Asaf Shabtai;Robert Moskovitch;Yuval Elovici;Chanan Glezer

  • Detecting unknown malicious code by applying classification techniques on OpCode patterns

    Asaf Shabtai;Robert Moskovitch;Clint Feher;Shlomi Dolev

  • Unknown Malcode Detection Using OPCODE Representation

    Robert Moskovitch;Clint Feher;Nir Tzachar;Eugene Berger

  • User identity verification via mouse dynamics

    Clint Feher;Yuval Elovici;Robert Moskovitch;Lior Rokach

  • A framework for a distributed, hybrid, multiple-ontology clinical-guideline library, and automated guideline-support tools

    Yuval Shahar;Ohad Young;Erez Shalom;Maya Galperin

  • Medical temporal-knowledge discovery via temporal abstraction.

    Robert Moskovitch;Yuval Shahar

  • Detection of unknown computer worms based on behavioral classification of the host

    Robert Moskovitch;Yuval Elovici;Lior Rokach

  • Identity theft, computers and behavioral biometrics

    Robert Moskovitch;Clint Feher;Arik Messerman;Niklas Kirschnick

  • Classification-driven temporal discretization of multivariate time series

    Robert Moskovitch;Yuval Shahar

  • Unknown malcode detection via text categorization and the imbalance problem

    R. Moskovitch;D. Stopel;C. Feher;N. Nissim

  • Novel active learning methods for enhanced PC malware detection in windows OS

    Nir Nissim;Robert Moskovitch;Lior Rokach;Yuval Elovici

  • Classification of multivariate time series via temporal abstraction and time intervals mining

    Robert Moskovitch;Yuval Shahar

  • Fast time intervals mining using the transitivity of temporal relations

    Robert Moskovitch;Yuval Shahar

  • Method and system for detecting malicious behavioral patterns in a computer, using machine learning

    Robert Moskovitch;Dima Stopel;Zvi Boger;Yuval Shahar

  • Applying Machine Learning Techniques for Detection of Malicious Code in Network Traffic

    Yuval Elovici;Asaf Shabtai;Robert Moskovitch;Gil Tahan

  • DEGEL: A Hybrid, Multiple-Ontology Framework for Specification and Retrieval of Clinical Guidelines

    Yuval Shahar;Ohad Young;Erez Shalom;Alon Mayaffit

  • Unknown malcode detection and the imbalance problem

    Robert Moskovitch;Dima Stopel;Clint Feher;Nir Nissim

  • Detecting unknown computer worm activity via support vector machines and active learning

    Nir Nissim;Robert Moskovitch;Lior Rokach;Yuval Elovici

  • Continuous Verification Using Keystroke Dynamics

    Tomer Shimshon;Robert Moskovitch;Lior Rokach;Yuval Elovici

  • Identity theft, computers and behavioral biometrics

    Robert Moskovitch;Clint Feher;Arik Messerman;Niklas Kirschnick

Frequent Co-Authors

Yuval Elovici
Yuval Elovici Ben-Gurion University of the Negev
Yuval Shahar
Yuval Shahar Ben-Gurion University of the Negev
Lior Rokach
Lior Rokach Ben-Gurion University of the Negev
George Hripcsak
George Hripcsak Columbia University
Asaf Shabtai
Asaf Shabtai Ben-Gurion University of the Negev
Cesare Gessler
Cesare Gessler ETH Zurich
Ilaria Pertot
Ilaria Pertot University of Trento
Shlomi Dolev
Shlomi Dolev Ben-Gurion University of the Negev
Jian Pei
Jian Pei Duke University
Carol Friedman
Carol Friedman Columbia University

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