World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
54
Citations
14758
World Ranking
2246
National Ranking
879

Computer Science

D-Index
55
Citations
15169
World Ranking
4234
National Ranking
1999

Nam Sung Kim publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Nam Sung Kim sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 314 publications — 60th percentile

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

The last bar groups every scientist with 1,065 publications or more.

Nam Sung Kim D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Nam Sung Kim sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 54 D-Index — 68th percentile

68% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2020 - ACM Fellow For contribution to design and modeling of power-efficient computer architectures
  • 2016 - IEEE Fellow For contribution to circuits and architectures for power-efficient microprocessors

Overview

Nam Sung Kim is affiliated with the University of Illinois at Urbana-Champaign in the United States. Their research spans fields including computer science and engineering, with a particular focus on areas such as computer networks and communications, electrical and electronic engineering, hardware and architecture, information systems, and artificial intelligence.

The scientist's work addresses several key topics: parallel computing and optimization techniques, advanced data storage technologies, semiconductor materials and devices, cloud computing and resource management, advanced memory and neural computing, ferroelectric and negative capacitance devices, and caching and content delivery.

Frequent co-authors collaborating with Nam Sung Kim are Chihun Song, Ipoom Jeong, Houxiang Ji, Youjie Li, and Jung Ho Ahn.

Nam Sung Kim has published a significant number of articles in various academic venues, with notable frequent publication venues including:

  • arXiv (Cornell University)
  • IEEE Computer Architecture Letters
  • IEEE Micro
  • IEEE Transactions on Computers
  • IEEE Journal of Solid-State Circuits

Selected recent papers by Nam Sung Kim include:

  • Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM, 2021, IEEE Micro
  • Aquabolt-XL HBM2-PIM, LPDDR5-PIM With In-Memory Processing, and AXDIMM With Acceleration Buffer, 2022, IEEE Micro
  • A 16-GB 640-GB/s HBM2E DRAM With a Data-Bus Window Extension Technique and a Synergetic On-Die ECC Scheme, 2020, IEEE Journal of Solid-State Circuits
  • DML: Dynamic Partial Reconfiguration With Scalable Task Scheduling for Multi-Applications on FPGAs, 2021, IEEE Transactions on Computers
  • BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling, 2022, arXiv (Cornell University)

Nam Sung Kim has received recognition for contributions to their field, including being named an ACM Fellow in 2020 for work on the design and modeling of power-efficient computer architectures. In 2016, they were also elected IEEE Fellow for contributions to circuits and architectures for power-efficient microprocessors.

Best Publications

  • Razor: a low-power pipeline based on circuit-level timing speculation

    Dan Ernst;Nam Sung Kim;Shidhartha Das;Sanjay Pant

  • Leakage current: Moore's law meets static power

    N.S. Kim;T. Austin;D. Baauw;T. Mudge

  • Drowsy caches: simple techniques for reducing leakage power

    Krisztián Flautner;Nam Sung Kim;Steve Martin;David Blaauw

  • GPUWattch: enabling energy optimizations in GPGPUs

    Jingwen Leng;Tayler Hetherington;Ahmed ElTantawy;Syed Gilani

  • Approximate Computing: A Survey

    Qiang Xu;Todd Mytkowicz;Nam Sung Kim

  • Razor: circuit-level correction of timing errors for low-power operation

    D. Ernst;S. Das;S. Lee;D. Blaauw

  • Energy-Efficient and Metastability-Immune Resilient Circuits for Dynamic Variation Tolerance

    Keith A. Bowman;James W. Tschanz;Nam Sung Kim;Janice C. Lee

  • NDA: Near-DRAM acceleration architecture leveraging commodity DRAM devices and standard memory modules

    Amin Farmahini-Farahani;Jung Ho Ahn;Katherine Morrow;Nam Sung Kim

  • Energy-Efficient Approximate Multiplication for Digital Signal Processing and Classification Applications

    Srinivasan Narayanamoorthy;Hadi Asghari Moghaddam;Zhenhong Liu;Taejoon Park

  • Adaptive Frequency and Biasing Techniques for Tolerance to Dynamic Temperature-Voltage Variations and Aging

    J. Tschanz;Nam Sung Kim;S. Dighe;J. Howard

  • Circuit and microarchitectural techniques for reducing cache leakage power

    Nam Sung Kim;K. Flautner;D. Blaauw;T. Mudge

  • Drowsy instruction caches. Leakage power reduction using dynamic voltage scaling and cache sub-bank prediction

    Nam Sung Kim;Krisztián Flautner;David Blaauw;Trevor Mudge

  • The case for GPGPU spatial multitasking

    Jacob T. Adriaens;Katherine Compton;Nam Sung Kim;Michael J. Schulte

  • Yield-driven near-threshold SRAM design

    Gregory K. Chen;David Blaauw;Trevor Mudge;Dennis Sylvester

  • Hardware Architecture and Software Stack for PIM Based on Commercial DRAM Technology : Industrial Product

    Sukhan Lee;Shin-haeng Kang;Jaehoon Lee;Hyeonsu Kim

  • Power-efficient computing for compute-intensive GPGPU applications

    S. Z. Gilani;Nam Sung Kim;M. J. Schulte

  • 25.4 A 20nm 6GB Function-In-Memory DRAM, Based on HBM2 with a 1.2TFLOPS Programmable Computing Unit Using Bank-Level Parallelism, for Machine Learning Applications

    Young-Cheon Kwon;Suk Han Lee;Jaehoon Lee;Sang-Hyuk Kwon

  • Wordline & Bitline Pulsing Schemes for Improving SRAM Cell Stability in Low-Vcc 65nm CMOS Designs

    M. Khellah;Y. Ye;N. Kim;D. Somasekhar

  • VARIUS-NTV: A microarchitectural model to capture the increased sensitivity of manycores to process variations at near-threshold voltages

    Ulya R. Karpuzcu;Krishna B. Kolluru;Nam Sung Kim;Josep Torrellas

  • GPU register file virtualization

    Hyeran Jeon;Gokul Subramanian Ravi;Nam Sung Kim;Murali Annavaram

  • Optimizing throughput of power- and thermal-constrained multicore processors using DVFS and per-core power-gating

    Jungseob Lee;Nam Sung Kim

  • Chameleon: versatile and practical near-DRAM acceleration architecture for large memory systems

    Hadi Asghari-Moghaddam;Young Hoon Son;Jung Ho Ahn;Nam Sung Kim

Frequent Co-Authors

Trevor Mudge
Trevor Mudge University of Michigan–Ann Arbor
Vivek De
Vivek De Intel (United States)
Michael J. Schulte
Michael J. Schulte Advanced Micro Devices (United States)
Muhammad M. Khellah
Muhammad M. Khellah Intel (United States)
Dinesh Somasekhar
Dinesh Somasekhar Intel (United States)
Jung Ho Ahn
Jung Ho Ahn Seoul National University
Tanay Karnik
Tanay Karnik Intel (United States)
Mikko H. Lipasti
Mikko H. Lipasti University of Wisconsin–Madison
David Blaauw
David Blaauw University of Michigan–Ann Arbor
Hadi Esmaeilzadeh
Hadi Esmaeilzadeh 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

For students pursuing Electronics and Electrical Engineering in the USA, exploring related online degrees can broaden career prospects. Many roles in this field suit individuals who thrive in focused, independent work environments. The best jobs for introverts often align well with technical engineering positions, where analytical skills and problem-solving are crucial.

Additionally, combining engineering knowledge with management skills is increasingly valuable. Enrolling in a bachelor project management program online can equip graduates to lead teams and oversee complex projects efficiently.

For working professionals or those looking to accelerate their education, an accelerated online degrees format offers flexibility without sacrificing quality. Programs such as a project management degree online fast enable students to gain credentials quickly and adapt to evolving industry demands.

Exploring these degrees alongside traditional engineering paths can open new doors, blending technical expertise with leadership skills essential in today’s competitive job market.

Best Scientists Citing Nam Sung Kim

Trending Scientists

Recently Published Articles