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Yongpan Liu

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Electronics and Electrical Engineering 40 4457 4275 671 669 282 7514
Computer Science 39 9662 9385 1217 1211 281 7498

Yongpan Liu publications per year

The chart shows the history of publications by Yongpan Liu between 2005 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Yongpan Liu published across 21 years, from 2005 to 2025, averaging 17.9 papers a year. Output peaked at 42 publications in 2023. 69 of the 376 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2005 to 2025. Vertical axis: number of publications, 0 to 42. Peak 42 publications in 2023. 2005: 1 publication 2006: 5 publications 2007: 3 publications 2008: 1 publication 2009: 5 publications 2010: 8 publications 2011: 4 publications 2012: 15 publications 2013: 4 publications 2014: 9 publications 2015: 26 publications 2016: 27 publications 2017: 32 publications 2018: 24 publications 2019: 26 publications 2020: 25 publications 2021: 23 publications 2022: 27 publications 2023: 42 publications 2024: 32 publications 2025: 37 publications
2005 2025

376 publications in total across all disciplines

View publications per year as a table
Yongpan Liu: publications per year, 2005 to 2025
Year Publications
2005 1
2006 5
2007 3
2008 1
2009 5
2010 8
2011 4
2012 15
2013 4
2014 9
2015 26
2016 27
2017 32
2018 24
2019 26
2020 25
2021 23
2022 27
2023 42
2024 32
2025 37
Total 376
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Yongpan Liu 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 Yongpan Liu sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 53 bars. Horizontal axis: publications, 34–53 to 1,065+. Vertical axis: number of scientists, 0 to 445. Most scientists, 445, have 174–193 publications. The last bar groups every scientist with 1,065 publications or more. The highlighted bar, 274–293 publications, is where this scientist sits. 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
34–53 publications 1,065+

This scientist: 282 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Electronics and Electrical Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
Publications Scientists This scientist
34–53 24
54–73 52
74–93 114
94–113 203
114–133 269
134–153 355
154–173 403
174–193 445
194–213 430
214–233 431
234–253 399
254–273 366
274–293 335 282
294–313 300
314–333 276
334–353 250
354–373 214
374–393 187
394–413 152
414–433 169
434–453 147
454–473 111
474–493 117
494–513 103
514–533 99
534–553 92
554–573 75
574–593 58
594–613 69
614–633 50
634–653 62
654–673 54
674–693 44
694–713 37
714–733 28
734–753 26
754–773 26
774–793 19
794–813 23
814–833 20
834–853 16
854–873 20
874–893 11
894–913 11
914–933 16
934–953 13
954–973 10
974–993 11
994–1,013 9
1,014–1,033 9
1,034–1,053 10
1,054–1,064 6
1,065+ 99
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Yongpan Liu 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 Yongpan Liu sits on this spectrum.

No. of scientists
50 100 150 200 250
Bar chart with 82 bars. Horizontal axis: D-Index, 30 to 111+. Vertical axis: number of scientists, 0 to 263. Most scientists, 263, have 32 D-Index. The last bar groups every scientist with 111 D-Index or more. The highlighted bar, 40 D-Index, is where this scientist sits. 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.

View D-Index distribution as a table
Number of Electronics and Electrical Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
D-Index Scientists This scientist
30 178
31 257
32 263
33 262
34 244
35 236
36 211
37 220
38 214
39 214
40 205 40
41 187
42 194
43 201
44 155
45 189
46 148
47 160
48 134
49 130
50 141
51 156
52 108
53 130
54 112
55 97
56 111
57 102
58 108
59 120
60 103
61 93
62 92
63 74
64 77
65 73
66 64
67 69
68 60
69 39
70 57
71 59
72 46
73 49
74 38
75 35
76 32
77 35
78 31
79 22
80 34
81 31
82 34
83 23
84 18
85 30
86 19
87 19
88 20
89 8
90 17
91 7
92 14
93 9
94 15
95 10
96 12
97 10
98 10
99 12
100 16
101 5
102 7
103 7
104 8
105 9
106 13
107 4
108 5
109 10
110 8
111+ 96
Download as CSV

Overview

Yongpan Liu is affiliated with Tsinghua University in China, with a research focus that spans engineering and computer science, particularly within electrical and electronic engineering. Their academic work includes a strong emphasis on advanced memory and neural computing, as well as semiconductor materials and devices.

The scientist's recent publication record shows a range of studies covering topics such as nonvolatile computing, structured pruning for deep neural networks, and device-level innovations in resistive random-access memory (RRAM). Notable recent papers include:

  • Propionate alleviates myocardial ischemia-reperfusion injury aggravated by Angiotensin II dependent on caveolin-1/ACE2 axis through GPR41 (2022) in International Journal of Biological Sciences
  • STICKER-IM: A 65 nm Computing-in-Memory NN Processor Using Block-Wise Sparsity Optimization and Inter/Intra-Macro Data Reuse (2022) in IEEE Journal of Solid-State Circuits
  • StructADMM: Achieving Ultrahigh Efficiency in Structured Pruning for DNNs (2021) in IEEE Transactions on Neural Networks and Learning Systems
  • Efficient and Robust Nonvolatile Computing-In-Memory Based on Voltage Division in 2T2R RRAM With Input-Dependent Sensing Control (2021) in IEEE Transactions on Circuits & Systems II Express Briefs
  • An Ultracompact Switching-Voltage-Based Fully Reconfigurable RRAM PUF With Low Native Instability (2020) in IEEE Transactions on Electron Devices

Yongpan Liu frequently collaborates with several coauthors, including Huazhong Yang, Xueqing Li, Jinshan Yue, Wenyu Sun, and Xiaoyu Feng.

The most common publication venues for their work are:

  • arXiv (Cornell University)
  • IEEE Journal of Solid-State Circuits
  • IEEE Transactions on Circuits & Systems II Express Briefs
  • IEEE Transactions on Circuits and Systems I Regular Papers
  • IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems

Main fields of study associated with Yongpan Liu's work include:

  • Engineering
  • Computer Science

Their subfields of study highlight a concentration on:

  • Electrical and Electronic Engineering
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Hardware and Architecture
  • Molecular Biology

Yongpan Liu's research topics encompass:

  • Advanced Memory and Neural Computing
  • Ferroelectric and Negative Capacitance Devices
  • Advanced Neural Network Applications
  • Semiconductor materials and devices
  • Parallel Computing and Optimization Techniques
  • Physical Unclonable Functions (PUFs) and Hardware Security
  • Neural Networks and Reservoir Computing

Best Publications

  • PRIME: a novel processing-in-memory architecture for neural network computation in ReRAM-based main memory

    Ping Chi;Shuangchen Li;Cong Xu;Tao Zhang

  • Accurate temperature-dependent integrated circuit leakage power estimation is easy

    Yongpan Liu;Robert P. Dick;Li Shang;Huazhong Yang

  • Architecture exploration for ambient energy harvesting nonvolatile processors

    Kaisheng Ma;Yang Zheng;Shuangchen Li;Karthik Swaminathan

  • A 3us wake-up time nonvolatile processor based on ferroelectric flip-flops

    Unknown

  • Thermal vs Energy Optimization for DVFS-Enabled Processors in Embedded Systems

    Yongpan Liu;Huazhong Yang;R.P. Dick;H. Wang

  • GraphH: A Processing-in-Memory Architecture for Large-Scale Graph Processing

    Guohao Dai;Tianhao Huang;Yuze Chi;Jishen Zhao

  • Ambient energy harvesting nonvolatile processors: from circuit to system

    Yongpan Liu;Zewei Li;Hehe Li;Yiqun Wang

  • A 2.75-to-75.9TOPS/W Computing-in-Memory NN Processor Supporting Set-Associate Block-Wise Zero Skipping and Ping-Pong CIM with Simultaneous Computation and Weight Updating

    Jinshan Yue;Xiaoyu Feng;Yifan He;Yuxuan Huang

  • 14.3 A 65nm Computing-in-Memory-Based CNN Processor with 2.9-to-35.8TOPS/W System Energy Efficiency Using Dynamic-Sparsity Performance-Scaling Architecture and Energy-Efficient Inter/Intra-Macro Data Reuse

    Jinshan Yue;Zhe Yuan;Xiaoyu Feng;Yifan He

  • A global and updatable ECG beat classification system based on recurrent neural networks and active learning

    Guijin Wang;Chenshuang Zhang;Yongpan Liu;Huazhong Yang

  • Sticker: A 0.41-62.1 TOPS/W 8Bit Neural Network Processor with Multi-Sparsity Compatible Convolution Arrays and Online Tuning Acceleration for Fully Connected Layers

    Zhe Yuan;Jinshan Yue;Huanrui Yang;Zhibo Wang

  • Storage-Less and Converter-Less Photovoltaic Energy Harvesting With Maximum Power Point Tracking for Internet of Things

    Yiqun Wang;Yongpan Liu;Cong Wang;Zewei Li

  • A 462GOPs/J RRAM-based nonvolatile intelligent processor for energy harvesting IoE system featuring nonvolatile logics and processing-in-memory

    Fang Su;Wei-Hao Chen;Lixue Xia;Chieh-Pu Lo

  • Fixing the broken time machine: consistency-aware checkpointing for energy harvesting powered non-volatile processor

    Mimi Xie;Mengying Zhao;Chen Pan;Jingtong Hu

  • Hi-fi playback: tolerating position errors in shift operations of racetrack memory

    Chao Zhang;Guangyu Sun;Xian Zhang;Weiqi Zhang

  • Study on micro-atmospheric environment by coupling large eddy simulation with mesoscale model

    Y.S. Liu;Y.S. Liu;S.G. Miao;C.L. Zhang;G.X. Cui;G.X. Cui

  • STICKER: An Energy-Efficient Multi-Sparsity Compatible Accelerator for Convolutional Neural Networks in 65-nm CMOS

    Zhe Yuan;Yongpan Liu;Jinshan Yue;Yixiong Yang

  • Nonvolatile Processor Architecture Exploration for Energy-Harvesting Applications

    Kaisheng Ma;Xueqing Li;Shuangchen Li;Yongpan Liu

  • 4.7 A 65nm ReRAM-enabled nonvolatile processor with 6× reduction in restore time and 4× higher clock frequency using adaptive data retention and self-write-termination nonvolatile logic

    Yongpan Liu;Zhibo Wang;Albert Lee;Fang Su

  • Storage-less and converter-less maximum power point tracking of photovoltaic cells for a nonvolatile microprocessor

    Cong Wang;Naehyuck Chang;Younghyun Kim;Sangyoung Park

  • An energy-efficient heterogeneous dual-core processor for Internet of Things

    Zhibo Wang;Yongpan Liu;Yinan Sun;Yang Li

Frequent Co-Authors

Huazhong Yang
Huazhong Yang Tsinghua University
Chun Jason Xue
Chun Jason Xue Mohamed bin Zayed University of Artificial Intelligence
Meng-Fan Chang
Meng-Fan Chang National Tsing Hua University
Jingtong Hu
Jingtong Hu University of Pittsburgh
Yuan Xie
Yuan Xie Hong Kong University of Science and Technology
Yanzhi Wang
Yanzhi Wang Northeastern University
Xiaojun Guo
Xiaojun Guo Shanghai Jiao Tong University
Guangyu Sun
Guangyu Sun Peking University
Ya-Chin King
Ya-Chin King National Tsing Hua University
Suman Datta
Suman Datta Georgia Institute of Technology

External Links

Personal website of Yongpan Liu

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