World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6428
World Ranking
10679
National Ranking
669

Giuliano Casale 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 Giuliano Casale 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: 303 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Giuliano Casale 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 Giuliano Casale 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.

Research.com Recognitions

  • 2020 - ACM Senior Member

Overview

Giuliano Casale is affiliated with Imperial College London in the United Kingdom. Their research primarily focuses on computer science with significant contributions to subfields including computer networks and communications, information systems, management information systems, artificial intelligence, and statistics, probability, and uncertainty.

Their work extensively covers topics related to cloud computing and resource management, IoT and edge/fog computing, age of information optimization, software system performance and reliability, advanced queuing theory analysis, anomaly detection techniques and applications, and caching and content delivery.

Frequent co-authors collaborating with Giuliano Casale include Shreshth Tuli, Nicholas R. Jennings, Yicheng Gao, Alim Ul Gias, and Lulai Zhu.

Giuliano Casale's publication record spans various academic venues. They have a notable presence in:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Network and Service Management
  • ACM SIGMETRICS Performance Evaluation Review
  • ACM Transactions on Modeling and Performance Evaluation of Computing Systems

Selected recent papers authored or co-authored by Casale include:

  • "TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data," 2022, arXiv (Cornell University)
  • "TranAD," 2022, Proceedings of the VLDB Endowment
  • "AI augmented Edge and Fog computing: Trends and challenges," 2023, Journal of Network and Computer Applications
  • "Quality-Aware DevOps Research: Where Do We Stand?," 2021, IEEE Access
  • "PreGAN: Preemptive Migration Prediction Network for Proactive Fault-Tolerant Edge Computing," 2022, IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

The researcher has been recognized with the ACM Senior Member award in 2020.

Best Publications

  • TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

    Unknown

  • A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade

    Rajkumar Buyya;Satish Narayana Srirama;Giuliano Casale;Rodrigo Calheiros

  • Quality-of-service in cloud computing: modeling techniques and their applications

    Danilo Ardagna;Giuliano Casale;Michele Ciavotta;Juan F Pérez

  • MODAClouds: a model-driven approach for the design and execution of applications on multiple clouds

    Danilo Ardagna;Elisabetta Di Nitto;Giuliano Casale;Dana Petcu

  • JMT: performance engineering tools for system modeling

    Marco Bertoli;Giuliano Casale;Giuseppe Serazzi

  • HUNTER: AI based holistic resource management for sustainable cloud computing

    Shreshth Tuli;Sukhpal Singh Gill;Minxian Xu;Peter Garraghan

  • MODAClouds: A model-driven approach for the design and execution of applications on multiple Clouds

    Unknown

  • Burstiness in multi-tier applications: symptoms, causes, and new models

    Ningfang Mi;Giuliano Casale;Ludmila Cherkasova;Evgenia Smirni

  • An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems

    Pooyan Jamshidi;Giuliano Casale

  • Injecting realistic burstiness to a traditional client-server benchmark

    Ningfang Mi;Giuliano Casale;Ludmila Cherkasova;Evgenia Smirni

  • TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data

    Unknown

  • Modelling and Simulation Challenges in Internet of Things

    Gabor Kecskemeti;Giuliano Casale;Devki Nandan Jha;Justin Lyon

  • Markovian Workload Characterization for QoS Prediction in the Cloud

    Sergio Pacheco-Sanchez;Giuliano Casale;Bryan Scotney;Sally McClean

  • ATOM: Model-Driven Autoscaling for Microservices

    Alim Ul Gias;Giuliano Casale;Murray Woodside

  • Trace data characterization and fitting for Markov modeling

    Giuliano Casale;Eddy Z. Zhang;Evgenia Smirni

  • Evaluating Approaches to Resource Demand Estimation

    Simon Spinner;Giuliano Casale;Fabian Brosig;Samuel Kounev

  • Estimating service resource consumption from response time measurements

    Stephan Kraft;Sergio Pacheco-Sanchez;Giuliano Casale;Stephen Dawson

  • AI augmented Edge and Fog computing: Trends and challenges

    Unknown

  • KPC-Toolbox: Simple Yet Effective Trace Fitting Using Markovian Arrival Processes

    G. Casale;E.Z. Zhang;E. Smirni

  • Holistic resource management for sustainable and reliable cloud computing: An innovative solution to global challenge

    Sukhpal Singh Gill;Sukhpal Singh Gill;Peter Garraghan;Vlado Stankovski;Giuliano Casale

  • Evaluating Weighted Round Robin Load Balancing for Cloud Web Services

    Weikun Wang;Giuliano Casale

  • DICE: quality-driven development of data-intensive cloud applications

    G. Casale;D. Ardagna;M. Artac;F. Barbier

  • SLA-driven planning and optimization of enterprise applications

    Hui Li;Giuliano Casale;Tariq Ellahi

  • COSCO: Container Orchestration Using Co-Simulation and Gradient Based Optimization for Fog Computing Environments

    Shreshth Tuli;Shivananda R. Poojara;Satish N. Srirama;Giuliano Casale

  • Java Modelling Tools: an Open Source Suite for Queueing Network Modelling andWorkload Analysis

    M. Bertoli;G. Casale;G. Serazzri

Frequent Co-Authors

Evgenia Smirni
Evgenia Smirni William & Mary
Danilo Ardagna
Danilo Ardagna Polytechnic University of Milan
Paolo Cremonesi
Paolo Cremonesi Polytechnic University of Milan
Elisabetta Di Nitto
Elisabetta Di Nitto Polytechnic University of Milan
Stefano Zanero
Stefano Zanero Polytechnic University of Milan
Rajkumar Buyya
Rajkumar Buyya University of Melbourne
Richard R. Muntz
Richard R. Muntz University of California, Los Angeles
Pooyan Jamshidi
Pooyan Jamshidi University of South Carolina
Erol Gelenbe
Erol Gelenbe Institute of Theoretical and Applied Informatics

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