Runze Han

734 total citations
31 papers, 621 citations indexed

About

Runze Han is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Materials Chemistry. According to data from OpenAlex, Runze Han has authored 31 papers receiving a total of 621 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Electrical and Electronic Engineering, 7 papers in Artificial Intelligence and 4 papers in Materials Chemistry. Recurrent topics in Runze Han's work include Advanced Memory and Neural Computing (27 papers), Ferroelectric and Negative Capacitance Devices (21 papers) and Semiconductor materials and devices (5 papers). Runze Han is often cited by papers focused on Advanced Memory and Neural Computing (27 papers), Ferroelectric and Negative Capacitance Devices (21 papers) and Semiconductor materials and devices (5 papers). Runze Han collaborates with scholars based in China, United States and Macao. Runze Han's co-authors include Jinfeng Kang, Peng Huang, Xiaoyan Liu, Lifeng Liu, Zheng Zhou, Yudi Zhao, Zhe Chen, Sijie Chen, Wenjia Ma and Bin Gao and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and IEEE Transactions on Electron Devices.

In The Last Decade

Runze Han

31 papers receiving 606 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Runze Han China	14	595	211	66	58	55	31	621
Felix Cüppers Germany	9	495 0.8×	227 1.1×	39 0.6×	57 1.0×	77 1.4×	17	521
Hanchan Song South Korea	12	456 0.8×	214 1.0×	84 1.3×	29 0.5×	71 1.3×	27	480
Anne Siemon Germany	15	795 1.3×	418 2.0×	35 0.5×	40 0.7×	74 1.3×	26	815
Justin M. Correll United States	5	623 1.0×	237 1.1×	119 1.8×	52 0.9×	107 1.9×	6	646
Dana Wheeler United States	4	730 1.2×	372 1.8×	79 1.2×	76 1.3×	138 2.5×	9	751
Dabin Wu China	4	578 1.0×	163 0.8×	137 2.1×	60 1.0×	73 1.3×	7	636
Mamathamba Kalishettyhalli Mahadevaiah Germany	13	577 1.0×	214 1.0×	70 1.1×	45 0.8×	60 1.1×	33	592
Min-Woo Kwon South Korea	14	512 0.9×	203 1.0×	83 1.3×	46 0.8×	99 1.8×	55	607

Countries citing papers authored by Runze Han

Since Specialization

Citations

This map shows the geographic impact of Runze Han'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 Runze Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runze Han more than expected).

Fields of papers citing papers by Runze Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Runze Han. 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 Runze Han. The network helps show where Runze Han may publish in the future.

Co-authorship network of co-authors of Runze Han

This figure shows the co-authorship network connecting the top 25 collaborators of Runze Han. A scholar is included among the top collaborators of Runze Han 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 Runze Han. Runze Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yang, Bing Xiang, Hong Jiang, Juan Yu, et al.. (2025). Quantum leap in medical mentorship: exploring ChatGPT’s transition from textbooks to terabytes. Frontiers in Medicine. 12. 1517981–1517981. 3 indexed citations

Huang, Peng, et al.. (2023). An ultra-high-density and energy-efficient content addressable memory design based on 3D-NAND flash. Science China Information Sciences. 66(4). 15 indexed citations

Huang, Peng, et al.. (2022). Mixed-Precision Partial Differential Equation Solver Design Based on Nonvolatile Memory. IEEE Transactions on Electron Devices. 69(7). 3708–3715. 9 indexed citations

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

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

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

Han, Runze, Peng Huang, Zhen Dong, et al.. (2019). A Novel Convolution Computing Paradigm Based on NOR Flash Array With High Computing Speed and Energy Efficiency. IEEE Transactions on Circuits and Systems I Regular Papers. 66(5). 1692–1703. 37 indexed citations

Wu, Huaqiang, He Qian, Jinfeng Kang, et al.. (2019). An Improved RRAM-Based Binarized Neural Network With High Variation-Tolerated Forward/Backward Propagation Module. IEEE Transactions on Electron Devices. 67(2). 469–473. 18 indexed citations

Huang, Peng, Runze Han, & Jinfeng Kang. (2019). AI learns how to learn with TCAMs. Nature Electronics. 2(11). 493–494. 8 indexed citations

10.

Huang, Peng, Zheng Zhou, Runze Han, et al.. (2019). Hardware implementation of RRAM based binarized neural networks. APL Materials. 7(8). 14 indexed citations

11.

Zhang, Min, Peng Huang, Yizhou Zhang, et al.. (2019). FNSim: A Device-Circuit-Algorithm Codesigned Simulator for Flash based Neural Network. 1–4. 1 indexed citations

12.

Huang, Peng, Runze Han, Zheng Zhou, et al.. (2019). Hardware Implementation of Energy Efficient Deep Learning Neural Network Based on Nanoscale Flash Computing Array. Advanced Materials Technologies. 4(5). 11 indexed citations

13.

Zhang, Yizhou, et al.. (2019). An Improved Hardware Accelaration Architecture of Binary Neural Network With 1T1R Array Based Forward/Backward Propagation Module. 1–2. 5 indexed citations

14.

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

15.

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

16.

Han, Runze, Zheng Zhou, Peng Huang, et al.. (2018). An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory. Japanese Journal of Applied Physics. 57(4S). 04FE05–04FE05. 1 indexed citations

17.

Feng, Yulin, Peng Huang, Zheng Zhou, et al.. (2018). Ru-based Oxide Resistive Random Access Memory for BEOL-Compatible Novel NVM Applications. 61. 1–3. 2 indexed citations

18.

Han, Runze, Peng Huang, Yudi Zhao, et al.. (2017). Demonstration of Logic Operations in High-Performance RRAM Crossbar Array Fabricated by Atomic Layer Deposition Technique. Nanoscale Research Letters. 12(1). 37–37. 22 indexed citations

19.

Sun, Bing, et al.. (2010). Identification and application of current compliance failure phenomenon in RRAM device. 144–145. 10 indexed citations

20.

Gao, Bin, Huangwei Zhang, Shimeng Yu, et al.. (2006). Oxide-based RRAM: Uniformity improvement using a new material-oriented methodology. Symposium on VLSI Technology. 30–31. 25 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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