World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
18872
World Ranking
9472
National Ranking
98

Byung-Gon Chun 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 Byung-Gon Chun 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: 88 publications — 5th percentile

5% of scientists in this discipline score the same or lower.

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

Byung-Gon Chun 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 Byung-Gon Chun 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Byung-Gon Chun is affiliated with Seoul National University in South Korea and has established a research profile primarily in the field of Computer Science. Within this domain, Chun's work notably spans several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Hardware and Architecture, and Software.

Their recent scholarly contributions include multiple papers published in notable venues. Key publications include:

  • "Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning" (2020) published in arXiv (Cornell University)
  • "WindTunnel" (2021) published in Proceedings of the VLDB Endowment
  • "Apache Nemo: A Framework for Optimizing Distributed Data Processing" (2020) published in ACM Transactions on Computer Systems
  • "Hippo: Taming Hyper-parameter Optimization of Deep Learning with Stage Trees" (2020) published in arXiv (Cornell University)
  • "Accelerating Multi-Model Inference by Merging DNNs of Different Weights" (2020) published in arXiv (Cornell University)

The research topics covered in Chun's work broadly focus on advanced neural network applications, machine learning and data classification, parallel computing and optimization techniques, and domain adaptation and few-shot learning. Additional interests include software testing and debugging techniques, cloud computing and resource management, and distributed systems and fault tolerance.

  • Advanced Neural Network Applications
  • Machine Learning and Data Classification
  • Parallel Computing and Optimization Techniques
  • Domain Adaptation and Few-Shot Learning
  • Software Testing and Debugging Techniques
  • Cloud Computing and Resource Management
  • Distributed Systems and Fault Tolerance

Chun's recent collaborative efforts involve frequent co-authors who have contributed alongside in multiple research projects. These co-authors include:

  • Gyeong-In Yu (4 publications)
  • Joo Seong Jeong (3 publications)
  • Sehoon Kim (2 publications)
  • Ahnjae Shin (2 publications)
  • Do Yoon Kim (2 publications)

The principal publication venues for Chun's research are:

  • arXiv (Cornell University) with 4 publications
  • Proceedings of the VLDB Endowment with 2 publications
  • ACM Transactions on Computer Systems with 1 publication
  • The Justice with 1 publication

Best Publications

  • TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

    William Enck;Peter Gilbert;Seungyeop Han;Vasant Tendulkar

  • CloneCloud: elastic execution between mobile device and cloud

    Byung-Gon Chun;Sunghwan Ihm;Petros Maniatis;Mayur Naik

  • A data-oriented (and beyond) network architecture

    Teemu Koponen;Mohit Chawla;Byung-Gon Chun;Andrey Ermolinskiy

  • TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

    William Enck;Peter Gilbert;Byung-Gon Chun;Landon P. Cox

  • RouteBricks: exploiting parallelism to scale software routers

    Mihai Dobrescu;Norbert Egi;Katerina Argyraki;Byung-Gon Chun

  • Augmented smartphone applications through clone cloud execution

    Byung-Gon Chun;Petros Maniatis

  • Making sense of performance in data analytics frameworks

    Kay Ousterhout;Ryan Rasti;Sylvia Ratnasamy;Scott Shenker

  • TaintDroid: an information flow tracking system for real-time privacy monitoring on smartphones

    William Enck;Peter Gilbert;Byung-Gon Chun;Landon P. Cox

  • Efficient replica maintenance for distributed storage systems

    Byung-Gon Chun;Frank Dabek;Andreas Haeberlen;Emil Sit

  • Attested append-only memory: making adversaries stick to their word

    Byung-Gon Chun;Petros Maniatis;Scott Shenker;John Kubiatowicz

  • Heterogeneity-aware resource allocation and scheduling in the cloud

    Gunho Lee;Byung-Gon Chun;H. Katz

  • Vision: automated security validation of mobile apps at app markets

    Peter Gilbert;Byung-Gon Chun;Landon P. Cox;Jaeyeon Jung

  • Selfish caching in distributed systems: a game-theoretic analysis

    Byung-Gon Chun;Kamalika Chaudhuri;Hoeteck Wee;Marco Barreno

  • Dynamically partitioning applications between weak devices and clouds

    Byung-Gon Chun;Petros Maniatis

  • MegaPipe: a new programming interface for scalable network I/O

    Sangjin Han;Scott Marshall;Byung-Gon Chun;Sylvia Ratnasamy

  • An energy case for hybrid datacenters

    Byung-Gon Chun;Gianluca Iannaccone;Giuseppe Iannaccone;Randy Katz

  • Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression

    Ling Huang;Jinzhu Jia;Bin Yu;Byung-gon Chun

  • Characterizing selfishly constructed overlay routing networks

    Byung-Gon Chun;R. Fonseca;I. Stoica;J. Kubiatowicz

  • Proactive replication for data durability

    Emil Sit;Andreas Haeberlen;Frank Dabek;Byung-Gon Chun

  • Macroscope: end-point approach to networked application dependency discovery

    Lucian Popa;Byung-Gon Chun;Ion Stoica;Jaideep Chandrashekar

Frequent Co-Authors

Petros Maniatis
Petros Maniatis Google (United States)
John Kubiatowicz
John Kubiatowicz University of California, Berkeley
Scott Shenker
Scott Shenker University of California, Berkeley
Sylvia Ratnasamy
Sylvia Ratnasamy University of California, Berkeley
Mayur Naik
Mayur Naik University of Pennsylvania
Carlo Curino
Carlo Curino Microsoft (United States)
Raghu Ramakrishnan
Raghu Ramakrishnan Microsoft (United States)
Ling Huang
Ling Huang Intel (United States)
Ion Stoica
Ion Stoica University of California, Berkeley
Landon P. Cox
Landon P. Cox Duke University

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 career paths in Computer Science opens doors to a wide range of lucrative and flexible options. Many students are now considering online electrical engineering courses USA as a way to supplement their computer science knowledge and expand their expertise. These online programs make it easier to balance education with work or other commitments.

For those looking to quickly boost their credentials, obtaining easy certifications that pay well can be a fast track to in-demand positions in the tech industry. Certifications often require less time than traditional degrees and can help job seekers stand out.

Students focused on efficiency might also consider the fastest online master's degree options. These accelerated programs allow professionals to advance their education and career prospects in less time.

With technology fields constantly evolving, choosing from the most worthwhile masters degrees can lead to rewarding career outcomes. Leveraging online study, certifications, and high-demand degrees will set you on a successful pathway in Computer Science and related disciplines.

Best Scientists Citing Byung-Gon Chun

Trending Scientists

Recently Published Articles