World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
15989
World Ranking
3393
National Ranking
1646

David S. Rosenblum 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 David S. Rosenblum 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: 222 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

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

David S. Rosenblum 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 David S. Rosenblum 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: 59 D-Index — 77th percentile

77% 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

  • 2010 - ACM Fellow For contributions to software testing and distributed systems, and for service to the software engineering community.
  • 2006 - IEEE Fellow For contributions to scalable, distributed component- and event-based software systems.

Overview

David S. Rosenblum is affiliated with George Mason University in the United States. Their research focuses mainly on computer science and engineering, with a total of 31 publications in computer science and 9 in engineering.

The scientist's work spans several subfields, including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Building and Construction
  • Transportation

Key topics addressed in their research encompass:

  • Traffic Prediction and Management Techniques
  • Recommender Systems and Techniques
  • Human Mobility and Location-Based Analysis
  • Video Surveillance and Tracking Methods
  • Adversarial Robustness in Machine Learning
  • Data Stream Mining Techniques
  • Advanced Software Engineering Methodologies

David S. Rosenblum has published extensively in various venues. The most frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Big Data
  • IEEE Transactions on Software Engineering
  • IEEE Transactions on Dependable and Secure Computing

Recent papers authored or co-authored by Rosenblum include:

  • Directed Graph Convolutional Network, 2020, arXiv (Cornell University)
  • Fine-Grained Urban Flow Inference, 2020, IEEE Transactions on Knowledge and Data Engineering
  • Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting, 2022, IEEE Transactions on Knowledge and Data Engineering
  • Predicting Urban Water Quality with Ubiquitous Data - A Data-driven Approach, 2020, IEEE Transactions on Big Data
  • Quantitative Verification for Monitoring Event-Streaming Systems, 2020, IEEE Transactions on Software Engineering

Frequent co-authors who have collaborated multiple times with Rosenblum include:

  • Yuxuan Liang
  • Kun Ouyang
  • Yu Zheng
  • Junbo Zhang
  • Ye Liu

David S. Rosenblum has received several awards recognizing their contributions to software engineering and distributed systems. These honors include:

  • ACM Fellow (2010) for contributions to software testing and distributed systems, and service to the software engineering community
  • IEEE Fellow (2006) for contributions to scalable, distributed component- and event-based software systems

Best Publications

  • Design and evaluation of a wide-area event notification service

    Antonio Carzaniga;David S. Rosenblum;Alexander L. Wolf

  • An architecture-based approach to self-adaptive software

    P. Oreizy;M.M. Gorlick;R.N. Taylor;D. Heimhigner

  • From action to activity

    Ye Liu;Liqiang Nie;Li Liu;David S. Rosenblum

  • Achieving scalability and expressiveness in an Internet-scale event notification service

    Antonio Carzaniga;David S. Rosenblum;Alexander L. Wolf

  • Modeling software architectures in the Unified Modeling Language

    Nenad Medvidovic;David S. Rosenblum;David F. Redmiles;Jason E. Robbins

  • A practical approach to programming with assertions

    D.S. Rosenblum

  • A language and environment for architecture-based software development and evolution

    Nenad Medvidovic;David S. Rosenblum;Richard N. Taylor

  • TestTube: a system for selective regression testing

    Yih-Farn Chen;David S. Rosenblum;Kiem-Phong Vo

  • A design framework for Internet-scale event observation and notification

    David S. Rosenblum;Alexander L. Wolf

  • Action2Activity: recognizing complex activities from sensor data

    Ye Liu;Liqiang Nie;Lei Han;Luming Zhang

  • Component metadata for software engineering tasks

    Alessandro Orso;Mary Jean Harrold;David Rosenblum

  • Fortune teller: predicting your career path

    Ye Liu;Luming Zhang;Liqiang Nie;Yan Yan

  • Context-aware mobile music recommendation for daily activities

    Xinxi Wang;David Rosenblum;Ye Wang

  • Urban water quality prediction based on multi-task multi-view learning

    Ye Liu;Yu Zheng;Yuxuan Liang;Shuming Liu

  • Recognizing complex activities by a probabilistic interval-based model

    Li Liu;Li Cheng;Ye Liu;Yongpo Jia

  • Integrating architecture description languages with a standard design method

    Jason E. Robbins;Nenad Medvidovic;David F. Redmiles;David S. Rosenblum

  • MMKG: Multi-Modal Knowledge Graphs

    Ye Liu;Hui Li;Alberto Garcia-Duran;Mathias Niepert

  • Formal methods and testing: why the state-of-the art is not the state-of-the practice

    David S. Rosenblum

  • Using component metacontent to support the regression testing of component-based software

    A. Orso;M.J. Harrold;D. Rosenblum;G. Rothermel

  • Yeast: a general purpose event-action system

    B. Krishnamurthy;D.S. Rosenblum

  • A historical perspective on runtime assertion checking in software development

    Lori A. Clarke;David S. Rosenblum

Frequent Co-Authors

Alexander L. Wolf
Alexander L. Wolf University of California, Santa Cruz
Sebastian Elbaum
Sebastian Elbaum University of Virginia
Antonio Carzaniga
Antonio Carzaniga Universita della Svizzera Italiana
Nenad Medvidovic
Nenad Medvidovic University of Southern California
Sebastian Uchitel
Sebastian Uchitel University of Buenos Aires
Gregg Rothermel
Gregg Rothermel North Carolina State University
Richard N. Taylor
Richard N. Taylor University of California, Irvine
Alessandro Orso
Alessandro Orso Georgia Institute of Technology
Liqiang Nie
Liqiang Nie Shandong University
Yennun Huang
Yennun Huang Research Center for Information Technology Innovation, Academia Sinica

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