World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
12247
World Ranking
5801
National Ranking
2636

Changhoon Kim 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 Changhoon Kim 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: 97 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Changhoon Kim 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 Changhoon Kim 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

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

Overview

Changhoon Kim is affiliated with Intel in the United States and has contributed to research spanning multiple domains including computer science and engineering. Their work reflects an interdisciplinary approach with focus areas in network systems as well as materials chemistry.

The main fields of study for Changhoon Kim include Computer Science and Engineering. Within these broad areas, key subfields encompass Computer Networks and Communications, Electrical and Electronic Engineering, Materials Chemistry, Computer Vision and Pattern Recognition, and Artificial Intelligence.

Themes frequently addressed by Changhoon Kim's research include:

  • Interconnection Networks and Systems
  • Software-Defined Networks and 5G
  • Advanced Battery Materials and Technologies
  • Solid-state Spectroscopy and Crystallography
  • Thermal Expansion and Ionic Conductivity
  • Digital Media Forensic Detection
  • Adversarial Robustness in Machine Learning

Changhoon Kim has published papers in several venues, with the most frequent publication outlets being:

  • arXiv (Cornell University)
  • Energy storage materials
  • Journal of Power System Engineering
  • Korean System Dynamics Review

Sample recent publications include:

  • KTaCl6: High-voltage stable potassium-ion conducting chloride solid electrolyte, 2024, Energy storage materials
  • The nanoPU: Redesigning the CPU-Network Interface to Minimize RPC Tail Latency, 2020, arXiv (Cornell University)
  • A Study on the Design and Numerical Analysis of Gas Pressure Regulating Valve for LNG Ship, 2023, Journal of Power System Engineering
  • SFC: Near-Source Congestion Signaling and Flow Control, 2023, arXiv (Cornell University)
  • Enabling the Reflex Plane with the nanoPU, 2022, arXiv (Cornell University)

Frequent collaborators include Serhat Arslan, Stephen Ibanez, Alex Mallery, Theo Jepsen, and Muhammad Shahbaz. These partnerships appear in multiple publications, indicating recurring joint research efforts.

Best Publications

  • VL2: a scalable and flexible data center network

    Albert Greenberg;James R. Hamilton;Navendu Jain;Srikanth Kandula

  • NetCache: Balancing Key-Value Stores with Fast In-Network Caching

    Xin Jin;Xiaozhou Li;Haoyu Zhang;Robert Soulé

  • Sharing the data center network

    Alan Shieh;Srikanth Kandula;Albert Greenberg;Changhoon Kim

  • Floodless in seattle: a scalable ethernet architecture for large enterprises

    Changhoon Kim;Matthew Caesar;Jennifer Rexford

  • SilkRoad: Making Stateful Layer-4 Load Balancing Fast and Cheap Using Switching ASICs

    Rui Miao;Hongyi Zeng;Changhoon Kim;Jeongkeun Lee

  • HULA: Scalable Load Balancing Using Programmable Data Planes

    Naga Katta;Mukesh Hira;Changhoon Kim;Anirudh Sivaraman

  • Ananta: cloud scale load balancing

    Parveen Patel;Deepak Bansal;Lihua Yuan;Ashwin Murthy

  • VL2: a scalable and flexible data center network

    Albert Greenberg;James R. Hamilton;Navendu Jain;Srikanth Kandula

  • EyeQ: practical network performance isolation at the edge

    Vimalkumar Jeyakumar;Mohammad Alizadeh;David Mazières;Balaji Prabhakar

  • FlowRadar: a better NetFlow for data centers

    Yuliang Li;Rui Miao;Changhoon Kim;Minlan Yu

  • Language-Directed Hardware Design for Network Performance Monitoring

    Srinivas Narayana;Anirudh Sivaraman;Vikram Nathan;Prateesh Goyal

  • Packet Transactions: High-Level Programming for Line-Rate Switches

    Anirudh Sivaraman;Alvin Cheung;Mihai Budiu;Changhoon Kim

  • Netchain: scale-free sub-RTT coordination

    Xin Jin;Xiaozhou Li;Haoyu Zhang;Nate Foster

  • Interconnecting members of a virtual network

    Hasan Alkhatib;Changhoon Kim;Geoff Outhred;Deepak Bansal

  • PISCES: A Programmable, Protocol-Independent Software Switch

    Muhammad Shahbaz;Sean Choi;Ben Pfaff;Changhoon Kim

  • Agile data center network architecture

    Albert Greenberg;Parantap Lahiri;David A. Maltz;Parveen K. Patel

  • Seawall: performance isolation for cloud datacenter networks

    Alan Shieh;Srikanth Kandula;Albert Greenberg;Changhoon Kim

  • Scaling Distributed Machine Learning with In-Network Aggregation

    Amedeo Sapio;Marco Canini;Chen-Yu Ho;Jacob Nelson

  • Performance isolation for clouds

    Albert Greenberg;Alan Shieh;Srikanth Kandula;Changhoon Kim

  • Millions of little minions: using packets for low latency network programming and visibility

    Vimalkumar Jeyakumar;Mohammad Alizadeh;Yilong Geng;Changhoon Kim

  • SEATTLE: A Scalable Ethernet Architecture for Large Enterprises

    Changhoon Kim;Matthew Caesar;Jennifer Rexford

  • Packet Transactions: High-level Programming for Line-Rate Switches

    Anirudh Sivaraman;Mihai Budiu;Alvin Cheung;Changhoon Kim

Frequent Co-Authors

David A. Maltz
David A. Maltz Microsoft (United States)
Srikanth Kandula
Srikanth Kandula Microsoft (United States)
Jennifer Rexford
Jennifer Rexford Princeton University
Jeongkeun Lee
Jeongkeun Lee Intel (United States)
Albert Greenberg
Albert Greenberg Microsoft (United States)
David Mazières
David Mazières Stanford University
Ion Stoica
Ion Stoica University of California, Berkeley
Nick McKeown
Nick McKeown Stanford University
Minlan Yu
Minlan Yu Harvard 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

Choosing a career in Computer Science opens up numerous educational options, allowing students to tailor their academic paths to fit their goals. For those seeking a flexible and budget-friendly start, enrolling in an associate's degree program may be the quickest way to enter the tech workforce or prepare for transfer to a four-year university.

Many students and working professionals are also considering online affordable master's programs as a way to deepen their skills without interrupting their careers. These programs can enhance job prospects in specialized areas like software engineering, data science, or cybersecurity.

For those interested in leadership or academia, advanced degrees such as a doctorate in leadership or online educational leadership programs open doors to executive, administrative, and instructional roles. These pathways benefit from the flexibility and affordability of online learning while delivering a high level of academic rigor.

Best Scientists Citing Changhoon Kim

Trending Scientists

Recently Published Articles