World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
41
Citations
7062
World Ranking
4289
National Ranking
70

Kea-Tiong Tang 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 Kea-Tiong Tang 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: 232 publications — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Kea-Tiong Tang 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 Kea-Tiong Tang 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: 41 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Overview

Kea-Tiong Tang is affiliated with National Tsing Hua University in Taiwan and has contributed extensively in the field of engineering, with a particular emphasis on electrical and electronic engineering. Their research encompasses diverse subfields including biomedical engineering, cellular and molecular neuroscience, artificial intelligence, and computer vision and pattern recognition.

Their work focuses on topics such as advanced memory and neural computing, ferroelectric and negative capacitance devices, advanced chemical sensor technologies, semiconductor materials and devices, CCD and CMOS imaging sensors, neuroscience and neural engineering, and gas sensing nanomaterials and sensors.

They have a substantial publication record with papers appearing frequently in prominent venues. Key publication venues include:

  • IEEE Journal of Solid-State Circuits
  • 2022 IEEE International Solid-State Circuits Conference (ISSCC)
  • IEEE Transactions on Very Large Scale Integration (VLSI) Systems
  • IEEE Transactions on Biomedical Circuits and Systems
  • IEEE Transactions on Circuits & Systems II Express Briefs

Frequent collaborators in their research include Meng-Fan Chang, Chih-Cheng Hsieh, Chung-Chuan Lo, Ren-Shuo Liu, and Meysam Akbari.

Selected recent publications highlight key advancements in compute-in-memory technologies and AI edge devices:

  • "A CMOS-integrated compute-in-memory macro based on resistive random-access memory for AI edge devices", 2020, Nature Electronics
  • "A Local Computing Cell and 6T SRAM-Based Computing-in-Memory Macro With 8-b MAC Operation for Edge AI Chips", 2021, IEEE Journal of Solid-State Circuits
  • "A 28nm 1Mb Time-Domain Computing-in-Memory 6T-SRAM Macro with a 6.6ns Latency, 1241GOPS and 37.01TOPS/W for 8b-MAC Operations for Edge-AI Devices", 2022, 2022 IEEE International Solid-State Circuits Conference (ISSCC)
  • "An 8-Mb DC-Current-Free Binary-to-8b Precision ReRAM Nonvolatile Computing-in-Memory Macro using Time-Space-Readout with 1286.4-21.6TOPS/W for Edge-AI Devices", 2022, 2022 IEEE International Solid-State Circuits Conference (ISSCC)
  • "A four-megabit compute-in-memory macro with eight-bit precision based on CMOS and resistive random-access memory for AI edge devices", 2021, Nature Electronics

Best Publications

  • A review of sensor-based methods for monitoring hydrogen sulfide

    Sudhir Kumar Pandey;Ki-Hyun Kim;Kea-Tiong Tang

  • A 65nm 1Mb nonvolatile computing-in-memory ReRAM macro with sub-16ns multiply-and-accumulate for binary DNN AI edge processors

    Wei-Hao Chen;Kai-Xiang Li;Wei-Yu Lin;Kuo-Hsiang Hsu

  • 24.1 A 1Mb Multibit ReRAM Computing-In-Memory Macro with 14.6ns Parallel MAC Computing Time for CNN Based AI Edge Processors

    Cheng-Xin Xue;Wei-Hao Chen;Je-Syu Liu;Jia-Fang Li

  • 24.5 A Twin-8T SRAM Computation-In-Memory Macro for Multiple-Bit CNN-Based Machine Learning

    Xin Si;Jia-Jing Chen;Yung-Ning Tu;Wei-Hsing Huang

  • Towards a Chemiresistive Sensor-Integrated Electronic Nose: A Review

    Shih-Wen Chiu;Kea-Tiong Tang

  • CMOS-integrated memristive non-volatile computing-in-memory for AI edge processors

    Wei-Hao Chen;Chunmeng Dou;Kai-Xiang Li;Wei-Yu Lin

  • 15.4 A 22nm 2Mb ReRAM Compute-in-Memory Macro with 121-28TOPS/W for Multibit MAC Computing for Tiny AI Edge Devices

    Cheng-Xin Xue;Tsung-Yuan Huang;Je-Syu Liu;Ting-Wei Chang

  • A Twin-8T SRAM Computation-in-Memory Unit-Macro for Multibit CNN-Based AI Edge Processors

    Xin Si;Rui Liu;Shimeng Yu;Ren-Shuo Liu

  • 15.5 A 28nm 64Kb 6T SRAM Computing-in-Memory Macro with 8b MAC Operation for AI Edge Chips

    Xin Si;Yung-Ning Tu;Wei-Hsing Huanq;Jian-Wei Su

  • 16.3 A 28nm 384kb 6T-SRAM Computation-in-Memory Macro with 8b Precision for AI Edge Chips

    Jian-Wei Su;Yen-Chi Chou;Ruhui Liu;Ta-Wei Liu

  • A 22nm 4Mb 8b-Precision ReRAM Computing-in-Memory Macro with 11.91 to 195.7TOPS/W for Tiny AI Edge Devices

    Cheng-Xin Xue;Je-Min Hung;Hui-Yao Kao;Yen-Hsiang Huang

  • 15.2 A 28nm 64Kb Inference-Training Two-Way Transpose Multibit 6T SRAM Compute-in-Memory Macro for AI Edge Chips

    Jian-Wei Su;Xin Si;Yen-Chi Chou;Ting-Wei Chang

  • A CMOS-integrated compute-in-memory macro based on resistive random-access memory for AI edge devices

    Cheng-Xin Xue;Yen-Cheng Chiu;Ta-Wei Liu;Tsung-Yuan Huang

  • Development of a Portable Electronic Nose System for the Detection and Classification of Fruity Odors

    Kea-Tiong Tang;Shih-Wen Chiu;Chih-Heng Pan;Hung-Yi Hsieh

  • A Local Computing Cell and 6T SRAM-Based Computing-in-Memory Macro With 8-b MAC Operation for Edge AI Chips

    Xin Si;Yung-Ning Tu;Wei-Hsing Huang;Jian-Wei Su

  • A Battery-Less, Implantable Neuro-Electronic Interface for Studying the Mechanisms of Deep Brain Stimulation in Rat Models

    Yu-Po Lin;Chun-Yi Yeh;Pin-Yang Huang;Zong-Ye Wang

  • Embedded 1-Mb ReRAM-Based Computing-in- Memory Macro With Multibit Input and Weight for CNN-Based AI Edge Processors

    Cheng-Xin Xue;Ting-Wei Chang;Tung-Cheng Chang;Hui-Yao Kao

  • A 0.5-V Real-Time Computational CMOS Image Sensor With Programmable Kernel for Feature Extraction

    Tzu-Hsiang Hsu;Yi-Ren Chen;Ren-Shuo Liu;Chung-Chuan Lo

  • VLSI Implementation of a Bio-Inspired Olfactory Spiking Neural Network

    Hung-Yi Hsieh;Kea-Tiong Tang

  • A 4-Kb 1-to-8-bit Configurable 6T SRAM-Based Computation-in-Memory Unit-Macro for CNN-Based AI Edge Processors

    Yen-Cheng Chiu;Zhixiao Zhang;Jia-Jing Chen;Xin Si

  • Apparatus to provide Safety Checks for Neural Stimulation

    Robert Greenberg;Kelly Mcclure;James Little;Rongqing Dai

  • A Low-Power Electronic Nose Signal-Processing Chip for a Portable Artificial Olfaction System

    Kea-Tiong Tang;Shih-Wen Chiu;Meng-Fan Chang;Chih-Cheng Hsieh

Frequent Co-Authors

Chih-Cheng Hsieh
Chih-Cheng Hsieh National Tsing Hua University
Meng-Fan Chang
Meng-Fan Chang National Tsing Hua University
Robert J. Greenberg
Robert J. Greenberg Johns Hopkins University
Li-Chun Wang
Li-Chun Wang National Yang Ming Chiao Tung University
Ya-Chin King
Ya-Chin King National Tsing Hua University
Shimeng Yu
Shimeng Yu Georgia Institute of Technology
Yang Dan
Yang Dan University of California, Berkeley
Chih-I Wu
Chih-I Wu National Taiwan University
Ki-Hyun Kim
Ki-Hyun Kim Hanyang University
Mohamad Sawan
Mohamad Sawan Polytechnique Montréal

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