Xiaoyan Liu

2.8k total citations
144 papers, 2.2k citations indexed

About

Xiaoyan Liu is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Materials Chemistry. According to data from OpenAlex, Xiaoyan Liu has authored 144 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 136 papers in Electrical and Electronic Engineering, 18 papers in Cellular and Molecular Neuroscience and 18 papers in Materials Chemistry. Recurrent topics in Xiaoyan Liu's work include Advanced Memory and Neural Computing (79 papers), Ferroelectric and Negative Capacitance Devices (70 papers) and Semiconductor materials and devices (61 papers). Xiaoyan Liu is often cited by papers focused on Advanced Memory and Neural Computing (79 papers), Ferroelectric and Negative Capacitance Devices (70 papers) and Semiconductor materials and devices (61 papers). Xiaoyan Liu collaborates with scholars based in China, United States and Singapore. Xiaoyan Liu's co-authors include Jinfeng Kang, Peng Huang, Lifeng Liu, Bin Gao, Gang Du, Zheng Zhou, Runze Han, Bing Chen, Zhe Chen and Lang Zeng and has published in prestigious journals such as Advanced Materials, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Xiaoyan Liu

129 papers receiving 2.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xiaoyan Liu China 25 2.1k 612 337 243 210 144 2.2k
Riduan Khaddam-Aljameh Switzerland 8 1.5k 0.7× 340 0.6× 328 1.0× 152 0.6× 343 1.6× 16 1.6k
Alessandro Calderoni Italy 23 1.7k 0.8× 587 1.0× 292 0.9× 223 0.9× 181 0.9× 51 1.8k
Haitong Li China 25 1.9k 0.9× 504 0.8× 544 1.6× 277 1.1× 273 1.3× 71 2.4k
Adnan Mehonić United Kingdom 20 2.1k 1.0× 808 1.3× 332 1.0× 342 1.4× 253 1.2× 53 2.2k
Francesco Maria Puglisi Italy 26 2.4k 1.2× 484 0.8× 589 1.7× 253 1.0× 182 0.9× 123 2.6k
Peng Huang China 29 3.1k 1.4× 918 1.5× 363 1.1× 415 1.7× 329 1.6× 166 3.2k
Fabien Alibart France 22 2.0k 1.0× 980 1.6× 345 1.0× 330 1.4× 303 1.4× 63 2.2k
L. Perniola France 29 2.9k 1.4× 707 1.2× 855 2.5× 407 1.7× 196 0.9× 138 3.0k
Udayan Ganguly India 22 1.8k 0.8× 331 0.5× 335 1.0× 140 0.6× 202 1.0× 191 1.9k
Rohit S. Shenoy United States 15 2.2k 1.0× 500 0.8× 628 1.9× 399 1.6× 281 1.3× 31 2.4k

Countries citing papers authored by Xiaoyan Liu

Since Specialization
Citations

This map shows the geographic impact of Xiaoyan Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiaoyan Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoyan Liu more than expected).

Fields of papers citing papers by Xiaoyan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaoyan Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiaoyan Liu. The network helps show where Xiaoyan Liu may publish in the future.

Co-authorship network of co-authors of Xiaoyan Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoyan Liu. A scholar is included among the top collaborators of Xiaoyan Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaoyan Liu. Xiaoyan Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Yiyang, Zheng Zhou, Yanzhi Wang, et al.. (2025). CIMUS: 3D-Stacked Computing-in-Memory Under Image Sensor Architecture for Efficient Machine Vision. IEEE Transactions on Computers. 74(7). 2321–2333.
2.
Yu, Chenxi, Zheng Zhou, Peng Huang, et al.. (2025). First Demonstration of Double-Gated Ferroelectric Field-Effect-Transistor With TiO₂ Channel for Multi-Level Storage. IEEE Electron Device Letters. 46(8). 1329–1332.
3.
Liu, Xiaoyan. (2024). Refined Management Method for Engineering Cost Combining Artificial Intelligence Technology. Procedia Computer Science. 247. 503–510.
4.
Zhou, Zheng, et al.. (2024). Gate-controlled gain tuning of fully depleted silicon-on-insulator-based 1 T pixel for in-sensor white balance. Japanese Journal of Applied Physics. 63(2). 02SP93–02SP93. 1 indexed citations
5.
6.
Dong, Junchen, Dedong Han, Zheng Zhou, et al.. (2024). Thin-film transistor for temporal self-adaptive reservoir computing with closed-loop architecture. Science Advances. 10(7). eadl1299–eadl1299. 37 indexed citations
7.
Yu, Chenxi, et al.. (2024). Optimized MFS Stack With N-Doped TiO2 Channel and La-Doped HfO2 Ferroelectric Layer for Highly Stable FeFETs. IEEE Electron Device Letters. 45(11). 2213–2216. 1 indexed citations
8.
Zhou, Zheng, Yiyang Chen, Lifeng Liu, et al.. (2024). Specific ADC of NVM-Based Computation-in-Memory for Deep Neural Networks. IEEE Transactions on Circuits and Systems I Regular Papers. 71(12). 5387–5399. 1 indexed citations
9.
Li, Jiaqi, Zheng Zhou, Ruiqi Chen, et al.. (2023). Gate-controlled Gain Tuning of FDSOI-based 1T Pixel for In-Sensor White Balance. 2 indexed citations
10.
Li, Minghua, et al.. (2023). Stress effect on the leakage current distribution of ferroelectric Al0.7Sc0.3N across the wafer. Applied Physics Letters. 123(13). 10 indexed citations
11.
Huang, Peng, Ruiyi Li, Yizhou Zhang, et al.. (2023). Flash-based content addressable memory with L2 distance for memory-augmented neural network. iScience. 26(12). 108371–108371. 2 indexed citations
12.
Han, Runze, Peng Huang, Hong Hu, et al.. (2022). Floating Gate Transistor‐Based Accurate Digital In‐Memory Computing for Deep Neural Networks. SHILAP Revista de lepidopterología. 4(12). 4 indexed citations
13.
Feng, Yulin, Peng Huang, Yudi Zhao, et al.. (2021). Improvement of State Stability in Multi-Level Resistive Random-Access Memory (RRAM) Array for Neuromorphic Computing. IEEE Electron Device Letters. 42(8). 1168–1171. 33 indexed citations
14.
Huang, Peng, Yudi Zhao, Yulin Feng, et al.. (2020). A Seamless, Reconfigurable, and Highly Parallel In-Memory Stochastic Computing Approach With Resistive Random Access Memory Array. IEEE Transactions on Electron Devices. 68(1). 103–108. 10 indexed citations
15.
Huang, Peng, et al.. (2020). Efficient and Robust Spike-Driven Deep Convolutional Neural Networks Based on NOR Flash Computing Array. IEEE Transactions on Electron Devices. 67(6). 2329–2335. 26 indexed citations
16.
Cai, Linlin, Wangyong Chen, Yudi Zhao, et al.. (2019). A Physics-Based Analytic Model of Analog Switching Resistive Random Access Memory. IEEE Electron Device Letters. 41(2). 236–239. 7 indexed citations
17.
Huang, Peng, Runze Han, Zheng Zhou, et al.. (2019). Stateful Logic Operations in One-Transistor-One- Resistor Resistive Random Access Memory Array. IEEE Electron Device Letters. 40(9). 1538–1541. 44 indexed citations
18.
Zhao, Yudi, Peng Huang, Zheng Zhou, et al.. (2019). A Physics-Based Compact Model for CBRAM Retention Behaviors Based on Atom Transport Dynamics and Percolation Theory. IEEE Electron Device Letters. 40(4). 647–650. 17 indexed citations
19.
Huang, Peng, Zheng Zhou, Runze Han, et al.. (2018). Design and Hardware Implementation of Neuromorphic Systems With RRAM Synapses and Threshold-Controlled Neurons for Pattern Recognition. IEEE Transactions on Circuits and Systems I Regular Papers. 65(9). 2726–2738. 50 indexed citations
20.
Han, Runze, Peng Huang, Zheng Zhou, et al.. (2018). A novel ternary content addressable memory design based on resistive random access memory with high intensity and low search energy. Japanese Journal of Applied Physics. 57(4S). 04FE02–04FE02. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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