World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
90
Citations
21883
World Ranking
621
National Ranking
329

Gregory R. Ganger 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 Gregory R. Ganger 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: 321 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Gregory R. Ganger 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 Gregory R. Ganger 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: 90 D-Index — 96th percentile

96% 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

  • 2011 - IEEE Fellow For contributions to metadata integrity in file systems
  • 2007 - ACM Distinguished Member

Overview

Gregory R. Ganger is affiliated with Carnegie Mellon University in the United States, focusing primarily on computer science research. Their work spans various subfields within computer science, including computer networks and communications, information systems, artificial intelligence, materials chemistry, and computational theory and mathematics.

The scientist's research topics cover multiple advanced areas, prominently featuring advanced data storage technologies, cloud computing and resource management, caching and content delivery, stochastic gradient optimization techniques, cloud data security solutions, distributed and parallel computing systems, and age of information optimization.

Recent publications illustrate a consistent interest in cluster scheduling, storage systems, and energy efficiency in computing. Selected papers include:

  • Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning, 2020, arXiv (Cornell University)
  • The Case for Custom Storage Backends in Distributed Storage Systems, 2020, ACM Transactions on Storage
  • A Call for Research on Storage Emissions, 2024, ACM SIGEnergy Energy Informatics Review
  • PACEMAKER: Avoiding HeART attacks in storage clusters with disk-adaptive redundancy, 2021, arXiv (Cornell University)

These works reflect contributions to both theoretical and applied aspects of data storage, cluster scheduling, and storage system sustainability.

Gregory R. Ganger collaborates frequently with other researchers. Notable co-authors include George Amvrosiadis, Sara McAllister, Nathan Beckmann, Suhas Jayaram Subramanya, and Daniel S. Berger.

The scientist has published extensively in venues such as arXiv (Cornell University), ACM Transactions on Storage, ACM SIGEnergy Energy Informatics Review, IEEE International Conference on High Performance Computing, Data, and Analytics, and UNC Libraries.

Recognition for contributions to the field includes being named an IEEE Fellow in 2011 for contributions to metadata integrity in file systems and an ACM Distinguished Member since 2007.

Best Publications

  • Heterogeneity and dynamicity of clouds at scale: Google trace analysis

    Charles Reiss;Alexey Tumanov;Gregory R. Ganger;Randy H. Katz

  • Object-based storage

    M. Mesnier;G.R. Ganger;E. Riedel

  • PipeDream: generalized pipeline parallelism for DNN training

    Deepak Narayanan;Aaron Harlap;Amar Phanishayee;Vivek Seshadri

  • Safe and effective fine-grained TCP retransmissions for datacenter communication

    Vijay Vasudevan;Amar Phanishayee;Hiral Shah;Elie Krevat

  • Fault-scalable Byzantine fault-tolerant services

    Michael Abd-El-Malek;Gregory R. Ganger;Garth R. Goodson;Michael K. Reiter

  • The DiskSim Simulation Environment Version 4.0 Reference Manual

    John S. Bucy;Jiri Schindler;Steven W. Schlosser;Gregory R. Ganger

  • Application performance and flexibility on exokernel systems

    M. Frans Kaashoek;Dawson R. Engler;Gregory R. Ganger;Hector M. Briceño

  • Journaling versus soft updates: asynchronous meta-data protection in file systems

    Margo I. Seltzer;Gregory R. Ganger;M. Kirk McKusick;Keith A. Smith

  • Scheduling algorithms for modern disk drives

    Bruce L. Worthington;Gregory R. Ganger;Yale N. Patt

  • Self-securing storage: protecting data in compromised system

    John D. Strunk;Garth R. Goodson;Michael L. Scheinholtz;Craig A. N. Soules

  • Survivable information storage systems

    J.J. Wylie;M.W. Bigrigg;J.D. Strunk;G.R. Ganger

  • Metadata Efficiency in Versioning File Systems

    Craig A. N. Soules;Garth R. Goodson;John D. Strunk;Gregory R. Ganger

  • Measurement and analysis of TCP throughput collapse in cluster-based storage systems

    Amar Phanishayee;Elie Krevat;Vijay Vasudevan;David G. Andersen

  • GeePS: scalable deep learning on distributed GPUs with a GPU-specialized parameter server

    Henggang Cui;Hao Zhang;Gregory R. Ganger;Phillip B. Gibbons

  • Gaia: geo-distributed machine learning approaching LAN speeds

    Kevin Hsieh;Aaron Harlap;Nandita Vijaykumar;Dimitris Konomis

  • On-line extraction of SCSI disk drive parameters

    Bruce L. Worthington;Gregory R. Ganger;Yale N. Patt;John Wilkes

  • Argon: performance insulation for shared storage servers

    Matthew Wachs;Michael Abd-El-Malek;Eno Thereska;Gregory R. Ganger

  • Robust and flexible power-proportional storage

    Hrishikesh Amur;James Cipar;Varun Gupta;Gregory R. Ganger

  • Metadata Efficiency in a Comprehensive Versioning File System

    Craig A Soules;Garth R Goodson;John D Strunk;Gregory R Ganger

  • Efficient Byzantine-tolerant erasure-coded storage

    G.R. Goodson;J.J. Wylie;G.R. Ganger;M.K. Reiter

Frequent Co-Authors

Michael K. Reiter
Michael K. Reiter Duke University
Garth A. Gibson
Garth A. Gibson Carnegie Mellon University
Yale N. Patt
Yale N. Patt The University of Texas at Austin
Michael Kozuch
Michael Kozuch Intel (United States)
Phillip B. Gibbons
Phillip B. Gibbons Carnegie Mellon University
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
David G. Andersen
David G. Andersen Carnegie Mellon University
Eric P. Xing
Eric P. Xing Mohamed bin Zayed University of Artificial Intelligence
Vijay K. Vasudevan
Vijay K. Vasudevan Google (United States)
Pradeep K. Khosla
Pradeep K. Khosla University of California, San Diego

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees can help you tailor your Computer Science education to your career goals and lifestyle. Many students look for the fastest online degree to quickly enter the tech workforce or advance in their current roles. Accelerated programs let you gain skills rapidly, making them a great choice for those eager to start earning sooner.

Budget is another key concern. If cost is a priority, consider the cheapest online masters in artificial intelligence. These programs offer advanced specializations at a fraction of the traditional cost, letting you compete in a high-demand field without breaking the bank.

Choosing your specialization is important, too. Investigate the top degrees for the future to ensure your education aligns with long-term technology trends and career stability. Artificial intelligence, data science, and cybersecurity are consistently highlighted as promising pathways.

If you're balancing work and study, you may be interested in pursuing an easy online masters degree in a related field. These flexible programs can provide valuable credentials and increase your job options with less pressure and time commitment.

Best Scientists Citing Gregory R. Ganger

Trending Scientists

Recently Published Articles