World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
40
Citations
7768
World Ranking
4452
National Ranking
151

Computer Science

D-Index
45
Citations
8601
World Ranking
7182
National Ranking
63

Sungjoo Yoo 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 Sungjoo Yoo 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: 176 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

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

Sungjoo Yoo 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 Sungjoo Yoo 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: 40 D-Index — 36th percentile

36% of scientists in this discipline score the same or lower.

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

Overview

Sungjoo Yoo is affiliated with Seoul National University in South Korea and has made significant contributions to the field of computer science, with a focus on computer vision and artificial intelligence. Their research encompasses a variety of subfields and topics within these disciplines.

The main fields of study covered by their research include:

  • Computer Science

Subfields of study addressed in their work are:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Media Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

The primary topics of their research include:

  • Advanced Vision and Imaging
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Image Processing Techniques and Applications
  • Optical measurement and interference techniques
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Image Processing Techniques

Sungjoo Yoo has published extensively in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Access
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture notes in computer science

Some of the recent papers authored or co-authored by Sungjoo Yoo are:

  • Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • McDRAM v2: In-Dynamic Random Access Memory Systolic Array Accelerator to Address the Large Model Problem in Deep Neural Networks on the Edge, 2020, IEEE Access
  • Augmenting Few-Shot Learning With Supervised Contrastive Learning, 2021, IEEE Access
  • MFOS: Model-Free & One-Shot Object Pose Estimation, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • MetaMix: Meta-State Precision Searcher for Mixed-Precision Activation Quantization, 2024, Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators in their research include:

  • Eunhyeok Park
  • Euntae Choi
  • Hyunyoung Jung
  • Han-Byul Kim
  • Jongmin Lee

Best Publications

  • A scalable processing-in-memory accelerator for parallel graph processing

    Junwhan Ahn;Sungpack Hong;Sungjoo Yoo;Onur Mutlu

  • Compression of Deep Convolutional Neural Networks for Fast and Low Power Mobile Applications

    Yong-Deok Kim;Eunhyeok Park;Sungjoo Yoo;Taelim Choi

  • PIM-enabled instructions: a low-overhead, locality-aware processing-in-memory architecture

    Junwhan Ahn;Sungjoo Yoo;Onur Mutlu;Kiyoung Choi

  • Machine Learning at Facebook: Understanding Inference at the Edge

    Carole-Jean Wu;David Brooks;Kevin Chen;Douglas Chen

  • Weighted-Entropy-Based Quantization for Deep Neural Networks

    Eunhyeok Park;Junwhan Ahn;Sungjoo Yoo

  • Automatic generation and targeting of application specific operating systems and embedded systems software

    L. Gauthier;Sungjoo Yoo;A.A. Jerraya

  • Component-based design approach for multicore SoCs

    W. Cescirio;A. Baghdadi;L. Gauthier;D. Lyonnard

  • Automatic generation of application-specific architectures for heterogeneous multiprocessor system-on-chip

    Damien Lyonnard;Sungjoo Yoo;Amer Baghdadi;Ahmed A. Jerraya

  • Energy-efficient neural network accelerator based on outlier-aware low-precision computation

    Eunhyeok Park;Dongyoung Kim;Sungjoo Yoo

  • Multiprocessor SoC platforms: a component-based design approach

    W.O. Cesario;D. Lyonnard;G. Nicolescu;Y. Paviot

  • Value-Aware Quantization for Training and Inference of Neural Networks

    Eunhyeok Park;Sungjoo Yoo;Peter Vajda

  • Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications

    Jongsoo Park;Maxim Naumov;Protonu Basu;Summer Deng

  • Dual Motion Estimation for Frame Rate Up-Conversion

    Suk-Ju Kang;Sungjoo Yoo;Young Hwan Kim

  • Exploiting Spatial Dimensions of Latent in GAN for Real-time Image Editing

    Hyunsu Kim;Yunjey Choi;Junho Kim;Sungjoo Yoo

  • Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss

    Hyunsu Kim;Ho Young Jhoo;Eunhyeok Park;Sungjoo Yoo

  • Fine-Grained Semantics-Aware Representation Enhancement for Self-Supervised Monocular Depth Estimation

    Hyunyoung Jung;Eunhyeok Park;Sungjoo Yoo

  • ZeNA: Zero-Aware Neural Network Accelerator

    Dongyoung Kim;Junwhan Ahn;Sungjoo Yoo

  • DASCA: Dead Write Prediction Assisted STT-RAM Cache Architecture

    Junwhan Ahn;Sungjoo Yoo;Kiyoung Choi

  • Power management of hybrid DRAM/PRAM-based main memory

    Hyunsun Park;Sungjoo Yoo;Sunggu Lee

  • PowerViP: Soc power estimation framework at transaction level

    Ikhwan Lee;Hyunsuk Kim;Peng Yang;Sungjoo Yoo

  • Big/little deep neural network for ultra low power inference

    Eunhyeok Park;Dongyoung Kim;Soobeom Kim;Yong-Deok Kim

  • Making DRAM Stronger Against Row Hammering

    Mungyu Son;Hyunsun Park;Junwhan Ahn;Sungjoo Yoo

Frequent Co-Authors

Kiyoung Choi
Kiyoung Choi Seoul National University
Chanik Park
Chanik Park Pohang University of Science and Technology
Jung Ho Ahn
Jung Ho Ahn Seoul National University
Yangqing Jia
Yangqing Jia Alibaba Group (China)
Onur Mutlu
Onur Mutlu ETH Zurich
Tae-Lim Choi
Tae-Lim Choi Seoul National University
Kim Hazelwood
Kim Hazelwood Facebook (United States)
Norbert Wehn
Norbert Wehn Technical University of Kaiserslautern
Zhenyu Sun
Zhenyu Sun Beijing University of Chemical Technology

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